Actual source code: mpisbaij.c
1: #include <../src/mat/impls/baij/mpi/mpibaij.h>
2: #include <../src/mat/impls/sbaij/mpi/mpisbaij.h>
3: #include <../src/mat/impls/sbaij/seq/sbaij.h>
4: #include <petscblaslapack.h>
6: static PetscErrorCode MatDestroy_MPISBAIJ(Mat mat)
7: {
8: Mat_MPISBAIJ *baij = (Mat_MPISBAIJ *)mat->data;
10: PetscFunctionBegin;
11: PetscCall(PetscLogObjectState((PetscObject)mat, "Rows=%" PetscInt_FMT ",Cols=%" PetscInt_FMT, mat->rmap->N, mat->cmap->N));
12: PetscCall(MatStashDestroy_Private(&mat->stash));
13: PetscCall(MatStashDestroy_Private(&mat->bstash));
14: PetscCall(MatDestroy(&baij->A));
15: PetscCall(MatDestroy(&baij->B));
16: #if defined(PETSC_USE_CTABLE)
17: PetscCall(PetscHMapIDestroy(&baij->colmap));
18: #else
19: PetscCall(PetscFree(baij->colmap));
20: #endif
21: PetscCall(PetscFree(baij->garray));
22: PetscCall(VecDestroy(&baij->lvec));
23: PetscCall(VecScatterDestroy(&baij->Mvctx));
24: PetscCall(VecDestroy(&baij->slvec0));
25: PetscCall(VecDestroy(&baij->slvec0b));
26: PetscCall(VecDestroy(&baij->slvec1));
27: PetscCall(VecDestroy(&baij->slvec1a));
28: PetscCall(VecDestroy(&baij->slvec1b));
29: PetscCall(VecScatterDestroy(&baij->sMvctx));
30: PetscCall(PetscFree2(baij->rowvalues, baij->rowindices));
31: PetscCall(PetscFree(baij->barray));
32: PetscCall(PetscFree(baij->hd));
33: PetscCall(VecDestroy(&baij->diag));
34: PetscCall(VecDestroy(&baij->bb1));
35: PetscCall(VecDestroy(&baij->xx1));
36: #if defined(PETSC_USE_REAL_MAT_SINGLE)
37: PetscCall(PetscFree(baij->setvaluescopy));
38: #endif
39: PetscCall(PetscFree(baij->in_loc));
40: PetscCall(PetscFree(baij->v_loc));
41: PetscCall(PetscFree(baij->rangebs));
42: PetscCall(PetscFree(mat->data));
44: PetscCall(PetscObjectChangeTypeName((PetscObject)mat, NULL));
45: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatStoreValues_C", NULL));
46: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatRetrieveValues_C", NULL));
47: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatMPISBAIJSetPreallocation_C", NULL));
48: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatMPISBAIJSetPreallocationCSR_C", NULL));
49: #if defined(PETSC_HAVE_ELEMENTAL)
50: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatConvert_mpisbaij_elemental_C", NULL));
51: #endif
52: #if defined(PETSC_HAVE_SCALAPACK)
53: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatConvert_mpisbaij_scalapack_C", NULL));
54: #endif
55: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatConvert_mpisbaij_mpiaij_C", NULL));
56: PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatConvert_mpisbaij_mpibaij_C", NULL));
57: PetscFunctionReturn(PETSC_SUCCESS);
58: }
60: /* defines MatSetValues_MPI_Hash(), MatAssemblyBegin_MPI_Hash(), MatAssemblyEnd_MPI_Hash(), MatSetUp_MPI_Hash() */
61: #define TYPE SBAIJ
62: #define TYPE_SBAIJ
63: #include "../src/mat/impls/aij/mpi/mpihashmat.h"
64: #undef TYPE
65: #undef TYPE_SBAIJ
67: #if defined(PETSC_HAVE_ELEMENTAL)
68: PETSC_INTERN PetscErrorCode MatConvert_MPISBAIJ_Elemental(Mat, MatType, MatReuse, Mat *);
69: #endif
70: #if defined(PETSC_HAVE_SCALAPACK)
71: PETSC_INTERN PetscErrorCode MatConvert_SBAIJ_ScaLAPACK(Mat, MatType, MatReuse, Mat *);
72: #endif
74: /* This could be moved to matimpl.h */
75: static PetscErrorCode MatPreallocateWithMats_Private(Mat B, PetscInt nm, Mat X[], PetscBool symm[], PetscBool fill)
76: {
77: Mat preallocator;
78: PetscInt r, rstart, rend;
79: PetscInt bs, i, m, n, M, N;
80: PetscBool cong = PETSC_TRUE;
82: PetscFunctionBegin;
85: for (i = 0; i < nm; i++) {
87: PetscCall(PetscLayoutCompare(B->rmap, X[i]->rmap, &cong));
88: PetscCheck(cong, PetscObjectComm((PetscObject)B), PETSC_ERR_SUP, "Not for different layouts");
89: }
91: PetscCall(MatGetBlockSize(B, &bs));
92: PetscCall(MatGetSize(B, &M, &N));
93: PetscCall(MatGetLocalSize(B, &m, &n));
94: PetscCall(MatCreate(PetscObjectComm((PetscObject)B), &preallocator));
95: PetscCall(MatSetType(preallocator, MATPREALLOCATOR));
96: PetscCall(MatSetBlockSize(preallocator, bs));
97: PetscCall(MatSetSizes(preallocator, m, n, M, N));
98: PetscCall(MatSetUp(preallocator));
99: PetscCall(MatGetOwnershipRange(preallocator, &rstart, &rend));
100: for (r = rstart; r < rend; ++r) {
101: PetscInt ncols;
102: const PetscInt *row;
103: const PetscScalar *vals;
105: for (i = 0; i < nm; i++) {
106: PetscCall(MatGetRow(X[i], r, &ncols, &row, &vals));
107: PetscCall(MatSetValues(preallocator, 1, &r, ncols, row, vals, INSERT_VALUES));
108: if (symm && symm[i]) PetscCall(MatSetValues(preallocator, ncols, row, 1, &r, vals, INSERT_VALUES));
109: PetscCall(MatRestoreRow(X[i], r, &ncols, &row, &vals));
110: }
111: }
112: PetscCall(MatAssemblyBegin(preallocator, MAT_FINAL_ASSEMBLY));
113: PetscCall(MatAssemblyEnd(preallocator, MAT_FINAL_ASSEMBLY));
114: PetscCall(MatPreallocatorPreallocate(preallocator, fill, B));
115: PetscCall(MatDestroy(&preallocator));
116: PetscFunctionReturn(PETSC_SUCCESS);
117: }
119: PETSC_INTERN PetscErrorCode MatConvert_MPISBAIJ_Basic(Mat A, MatType newtype, MatReuse reuse, Mat *newmat)
120: {
121: Mat B;
122: PetscInt r;
124: PetscFunctionBegin;
125: if (reuse != MAT_REUSE_MATRIX) {
126: PetscBool symm = PETSC_TRUE, isdense;
127: PetscInt bs;
129: PetscCall(MatCreate(PetscObjectComm((PetscObject)A), &B));
130: PetscCall(MatSetSizes(B, A->rmap->n, A->cmap->n, A->rmap->N, A->cmap->N));
131: PetscCall(MatSetType(B, newtype));
132: PetscCall(MatGetBlockSize(A, &bs));
133: PetscCall(MatSetBlockSize(B, bs));
134: PetscCall(PetscLayoutSetUp(B->rmap));
135: PetscCall(PetscLayoutSetUp(B->cmap));
136: PetscCall(PetscObjectTypeCompareAny((PetscObject)B, &isdense, MATSEQDENSE, MATMPIDENSE, MATSEQDENSECUDA, ""));
137: if (!isdense) {
138: PetscCall(MatGetRowUpperTriangular(A));
139: PetscCall(MatPreallocateWithMats_Private(B, 1, &A, &symm, PETSC_TRUE));
140: PetscCall(MatRestoreRowUpperTriangular(A));
141: } else {
142: PetscCall(MatSetUp(B));
143: }
144: } else {
145: B = *newmat;
146: PetscCall(MatZeroEntries(B));
147: }
149: PetscCall(MatGetRowUpperTriangular(A));
150: for (r = A->rmap->rstart; r < A->rmap->rend; r++) {
151: PetscInt ncols;
152: const PetscInt *row;
153: const PetscScalar *vals;
155: PetscCall(MatGetRow(A, r, &ncols, &row, &vals));
156: PetscCall(MatSetValues(B, 1, &r, ncols, row, vals, INSERT_VALUES));
157: #if defined(PETSC_USE_COMPLEX)
158: if (A->hermitian == PETSC_BOOL3_TRUE) {
159: PetscInt i;
160: for (i = 0; i < ncols; i++) PetscCall(MatSetValue(B, row[i], r, PetscConj(vals[i]), INSERT_VALUES));
161: } else {
162: PetscCall(MatSetValues(B, ncols, row, 1, &r, vals, INSERT_VALUES));
163: }
164: #else
165: PetscCall(MatSetValues(B, ncols, row, 1, &r, vals, INSERT_VALUES));
166: #endif
167: PetscCall(MatRestoreRow(A, r, &ncols, &row, &vals));
168: }
169: PetscCall(MatRestoreRowUpperTriangular(A));
170: PetscCall(MatAssemblyBegin(B, MAT_FINAL_ASSEMBLY));
171: PetscCall(MatAssemblyEnd(B, MAT_FINAL_ASSEMBLY));
173: if (reuse == MAT_INPLACE_MATRIX) {
174: PetscCall(MatHeaderReplace(A, &B));
175: } else {
176: *newmat = B;
177: }
178: PetscFunctionReturn(PETSC_SUCCESS);
179: }
181: static PetscErrorCode MatStoreValues_MPISBAIJ(Mat mat)
182: {
183: Mat_MPISBAIJ *aij = (Mat_MPISBAIJ *)mat->data;
185: PetscFunctionBegin;
186: PetscCall(MatStoreValues(aij->A));
187: PetscCall(MatStoreValues(aij->B));
188: PetscFunctionReturn(PETSC_SUCCESS);
189: }
191: static PetscErrorCode MatRetrieveValues_MPISBAIJ(Mat mat)
192: {
193: Mat_MPISBAIJ *aij = (Mat_MPISBAIJ *)mat->data;
195: PetscFunctionBegin;
196: PetscCall(MatRetrieveValues(aij->A));
197: PetscCall(MatRetrieveValues(aij->B));
198: PetscFunctionReturn(PETSC_SUCCESS);
199: }
201: #define MatSetValues_SeqSBAIJ_A_Private(row, col, value, addv, orow, ocol) \
202: do { \
203: brow = row / bs; \
204: rp = aj + ai[brow]; \
205: ap = aa + bs2 * ai[brow]; \
206: rmax = aimax[brow]; \
207: nrow = ailen[brow]; \
208: bcol = col / bs; \
209: ridx = row % bs; \
210: cidx = col % bs; \
211: low = 0; \
212: high = nrow; \
213: while (high - low > 3) { \
214: t = (low + high) / 2; \
215: if (rp[t] > bcol) high = t; \
216: else low = t; \
217: } \
218: for (_i = low; _i < high; _i++) { \
219: if (rp[_i] > bcol) break; \
220: if (rp[_i] == bcol) { \
221: bap = ap + bs2 * _i + bs * cidx + ridx; \
222: if (addv == ADD_VALUES) *bap += value; \
223: else *bap = value; \
224: goto a_noinsert; \
225: } \
226: } \
227: if (a->nonew == 1) goto a_noinsert; \
228: PetscCheck(a->nonew != -1, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Inserting a new nonzero at global row/column (%" PetscInt_FMT ", %" PetscInt_FMT ") into matrix", orow, ocol); \
229: MatSeqXAIJReallocateAIJ(A, a->mbs, bs2, nrow, brow, bcol, rmax, aa, ai, aj, rp, ap, aimax, a->nonew, MatScalar); \
230: N = nrow++ - 1; \
231: /* shift up all the later entries in this row */ \
232: PetscCall(PetscArraymove(rp + _i + 1, rp + _i, N - _i + 1)); \
233: PetscCall(PetscArraymove(ap + bs2 * (_i + 1), ap + bs2 * _i, bs2 * (N - _i + 1))); \
234: PetscCall(PetscArrayzero(ap + bs2 * _i, bs2)); \
235: rp[_i] = bcol; \
236: ap[bs2 * _i + bs * cidx + ridx] = value; \
237: a_noinsert:; \
238: ailen[brow] = nrow; \
239: } while (0)
241: #define MatSetValues_SeqSBAIJ_B_Private(row, col, value, addv, orow, ocol) \
242: do { \
243: brow = row / bs; \
244: rp = bj + bi[brow]; \
245: ap = ba + bs2 * bi[brow]; \
246: rmax = bimax[brow]; \
247: nrow = bilen[brow]; \
248: bcol = col / bs; \
249: ridx = row % bs; \
250: cidx = col % bs; \
251: low = 0; \
252: high = nrow; \
253: while (high - low > 3) { \
254: t = (low + high) / 2; \
255: if (rp[t] > bcol) high = t; \
256: else low = t; \
257: } \
258: for (_i = low; _i < high; _i++) { \
259: if (rp[_i] > bcol) break; \
260: if (rp[_i] == bcol) { \
261: bap = ap + bs2 * _i + bs * cidx + ridx; \
262: if (addv == ADD_VALUES) *bap += value; \
263: else *bap = value; \
264: goto b_noinsert; \
265: } \
266: } \
267: if (b->nonew == 1) goto b_noinsert; \
268: PetscCheck(b->nonew != -1, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Inserting a new nonzero at global row/column (%" PetscInt_FMT ", %" PetscInt_FMT ") into matrix", orow, ocol); \
269: MatSeqXAIJReallocateAIJ(B, b->mbs, bs2, nrow, brow, bcol, rmax, ba, bi, bj, rp, ap, bimax, b->nonew, MatScalar); \
270: N = nrow++ - 1; \
271: /* shift up all the later entries in this row */ \
272: PetscCall(PetscArraymove(rp + _i + 1, rp + _i, N - _i + 1)); \
273: PetscCall(PetscArraymove(ap + bs2 * (_i + 1), ap + bs2 * _i, bs2 * (N - _i + 1))); \
274: PetscCall(PetscArrayzero(ap + bs2 * _i, bs2)); \
275: rp[_i] = bcol; \
276: ap[bs2 * _i + bs * cidx + ridx] = value; \
277: b_noinsert:; \
278: bilen[brow] = nrow; \
279: } while (0)
281: /* Only add/insert a(i,j) with i<=j (blocks).
282: Any a(i,j) with i>j input by user is ignored or generates an error
283: */
284: static PetscErrorCode MatSetValues_MPISBAIJ(Mat mat, PetscInt m, const PetscInt im[], PetscInt n, const PetscInt in[], const PetscScalar v[], InsertMode addv)
285: {
286: Mat_MPISBAIJ *baij = (Mat_MPISBAIJ *)mat->data;
287: MatScalar value;
288: PetscBool roworiented = baij->roworiented;
289: PetscInt i, j, row, col;
290: PetscInt rstart_orig = mat->rmap->rstart;
291: PetscInt rend_orig = mat->rmap->rend, cstart_orig = mat->cmap->rstart;
292: PetscInt cend_orig = mat->cmap->rend, bs = mat->rmap->bs;
294: /* Some Variables required in the macro */
295: Mat A = baij->A;
296: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
297: PetscInt *aimax = a->imax, *ai = a->i, *ailen = a->ilen, *aj = a->j;
298: MatScalar *aa = a->a;
300: Mat B = baij->B;
301: Mat_SeqBAIJ *b = (Mat_SeqBAIJ *)B->data;
302: PetscInt *bimax = b->imax, *bi = b->i, *bilen = b->ilen, *bj = b->j;
303: MatScalar *ba = b->a;
305: PetscInt *rp, ii, nrow, _i, rmax, N, brow, bcol;
306: PetscInt low, high, t, ridx, cidx, bs2 = a->bs2;
307: MatScalar *ap, *bap;
309: /* for stash */
310: PetscInt n_loc, *in_loc = NULL;
311: MatScalar *v_loc = NULL;
313: PetscFunctionBegin;
314: if (!baij->donotstash) {
315: if (n > baij->n_loc) {
316: PetscCall(PetscFree(baij->in_loc));
317: PetscCall(PetscFree(baij->v_loc));
318: PetscCall(PetscMalloc1(n, &baij->in_loc));
319: PetscCall(PetscMalloc1(n, &baij->v_loc));
321: baij->n_loc = n;
322: }
323: in_loc = baij->in_loc;
324: v_loc = baij->v_loc;
325: }
327: for (i = 0; i < m; i++) {
328: if (im[i] < 0) continue;
329: PetscCheck(im[i] < mat->rmap->N, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Row too large: row %" PetscInt_FMT " max %" PetscInt_FMT, im[i], mat->rmap->N - 1);
330: if (im[i] >= rstart_orig && im[i] < rend_orig) { /* this processor entry */
331: row = im[i] - rstart_orig; /* local row index */
332: for (j = 0; j < n; j++) {
333: if (im[i] / bs > in[j] / bs) {
334: if (a->ignore_ltriangular) {
335: continue; /* ignore lower triangular blocks */
336: } else SETERRQ(PETSC_COMM_SELF, PETSC_ERR_USER, "Lower triangular value cannot be set for sbaij format. Ignoring these values, run with -mat_ignore_lower_triangular or call MatSetOption(mat,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE)");
337: }
338: if (in[j] >= cstart_orig && in[j] < cend_orig) { /* diag entry (A) */
339: col = in[j] - cstart_orig; /* local col index */
340: brow = row / bs;
341: bcol = col / bs;
342: if (brow > bcol) continue; /* ignore lower triangular blocks of A */
343: if (roworiented) value = v[i * n + j];
344: else value = v[i + j * m];
345: MatSetValues_SeqSBAIJ_A_Private(row, col, value, addv, im[i], in[j]);
346: /* PetscCall(MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv)); */
347: } else if (in[j] < 0) {
348: continue;
349: } else {
350: PetscCheck(in[j] < mat->cmap->N, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Column too large: col %" PetscInt_FMT " max %" PetscInt_FMT, in[j], mat->cmap->N - 1);
351: /* off-diag entry (B) */
352: if (mat->was_assembled) {
353: if (!baij->colmap) PetscCall(MatCreateColmap_MPIBAIJ_Private(mat));
354: #if defined(PETSC_USE_CTABLE)
355: PetscCall(PetscHMapIGetWithDefault(baij->colmap, in[j] / bs + 1, 0, &col));
356: col = col - 1;
357: #else
358: col = baij->colmap[in[j] / bs] - 1;
359: #endif
360: if (col < 0 && !((Mat_SeqSBAIJ *)baij->A->data)->nonew) {
361: PetscCall(MatDisAssemble_MPISBAIJ(mat));
362: col = in[j];
363: /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */
364: B = baij->B;
365: b = (Mat_SeqBAIJ *)B->data;
366: bimax = b->imax;
367: bi = b->i;
368: bilen = b->ilen;
369: bj = b->j;
370: ba = b->a;
371: } else col += in[j] % bs;
372: } else col = in[j];
373: if (roworiented) value = v[i * n + j];
374: else value = v[i + j * m];
375: MatSetValues_SeqSBAIJ_B_Private(row, col, value, addv, im[i], in[j]);
376: /* PetscCall(MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv)); */
377: }
378: }
379: } else { /* off processor entry */
380: PetscCheck(!mat->nooffprocentries, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Setting off process row %" PetscInt_FMT " even though MatSetOption(,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) was set", im[i]);
381: if (!baij->donotstash) {
382: mat->assembled = PETSC_FALSE;
383: n_loc = 0;
384: for (j = 0; j < n; j++) {
385: if (im[i] / bs > in[j] / bs) continue; /* ignore lower triangular blocks */
386: in_loc[n_loc] = in[j];
387: if (roworiented) {
388: v_loc[n_loc] = v[i * n + j];
389: } else {
390: v_loc[n_loc] = v[j * m + i];
391: }
392: n_loc++;
393: }
394: PetscCall(MatStashValuesRow_Private(&mat->stash, im[i], n_loc, in_loc, v_loc, PETSC_FALSE));
395: }
396: }
397: }
398: PetscFunctionReturn(PETSC_SUCCESS);
399: }
401: static inline PetscErrorCode MatSetValuesBlocked_SeqSBAIJ_Inlined(Mat A, PetscInt row, PetscInt col, const PetscScalar v[], InsertMode is, PetscInt orow, PetscInt ocol)
402: {
403: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data;
404: PetscInt *rp, low, high, t, ii, jj, nrow, i, rmax, N;
405: PetscInt *imax = a->imax, *ai = a->i, *ailen = a->ilen;
406: PetscInt *aj = a->j, nonew = a->nonew, bs2 = a->bs2, bs = A->rmap->bs;
407: PetscBool roworiented = a->roworiented;
408: const PetscScalar *value = v;
409: MatScalar *ap, *aa = a->a, *bap;
411: PetscFunctionBegin;
412: if (col < row) {
413: if (a->ignore_ltriangular) PetscFunctionReturn(PETSC_SUCCESS); /* ignore lower triangular block */
414: else SETERRQ(PETSC_COMM_SELF, PETSC_ERR_USER, "Lower triangular value cannot be set for sbaij format. Ignoring these values, run with -mat_ignore_lower_triangular or call MatSetOption(mat,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE)");
415: }
416: rp = aj + ai[row];
417: ap = aa + bs2 * ai[row];
418: rmax = imax[row];
419: nrow = ailen[row];
420: value = v;
421: low = 0;
422: high = nrow;
424: while (high - low > 7) {
425: t = (low + high) / 2;
426: if (rp[t] > col) high = t;
427: else low = t;
428: }
429: for (i = low; i < high; i++) {
430: if (rp[i] > col) break;
431: if (rp[i] == col) {
432: bap = ap + bs2 * i;
433: if (roworiented) {
434: if (is == ADD_VALUES) {
435: for (ii = 0; ii < bs; ii++) {
436: for (jj = ii; jj < bs2; jj += bs) bap[jj] += *value++;
437: }
438: } else {
439: for (ii = 0; ii < bs; ii++) {
440: for (jj = ii; jj < bs2; jj += bs) bap[jj] = *value++;
441: }
442: }
443: } else {
444: if (is == ADD_VALUES) {
445: for (ii = 0; ii < bs; ii++) {
446: for (jj = 0; jj < bs; jj++) *bap++ += *value++;
447: }
448: } else {
449: for (ii = 0; ii < bs; ii++) {
450: for (jj = 0; jj < bs; jj++) *bap++ = *value++;
451: }
452: }
453: }
454: goto noinsert2;
455: }
456: }
457: if (nonew == 1) goto noinsert2;
458: PetscCheck(nonew != -1, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Inserting a new block index nonzero block (%" PetscInt_FMT ", %" PetscInt_FMT ") in the matrix", orow, ocol);
459: MatSeqXAIJReallocateAIJ(A, a->mbs, bs2, nrow, row, col, rmax, aa, ai, aj, rp, ap, imax, nonew, MatScalar);
460: N = nrow++ - 1;
461: high++;
462: /* shift up all the later entries in this row */
463: PetscCall(PetscArraymove(rp + i + 1, rp + i, N - i + 1));
464: PetscCall(PetscArraymove(ap + bs2 * (i + 1), ap + bs2 * i, bs2 * (N - i + 1)));
465: rp[i] = col;
466: bap = ap + bs2 * i;
467: if (roworiented) {
468: for (ii = 0; ii < bs; ii++) {
469: for (jj = ii; jj < bs2; jj += bs) bap[jj] = *value++;
470: }
471: } else {
472: for (ii = 0; ii < bs; ii++) {
473: for (jj = 0; jj < bs; jj++) *bap++ = *value++;
474: }
475: }
476: noinsert2:;
477: ailen[row] = nrow;
478: PetscFunctionReturn(PETSC_SUCCESS);
479: }
481: /*
482: This routine is exactly duplicated in mpibaij.c
483: */
484: static inline PetscErrorCode MatSetValuesBlocked_SeqBAIJ_Inlined(Mat A, PetscInt row, PetscInt col, const PetscScalar v[], InsertMode is, PetscInt orow, PetscInt ocol)
485: {
486: Mat_SeqBAIJ *a = (Mat_SeqBAIJ *)A->data;
487: PetscInt *rp, low, high, t, ii, jj, nrow, i, rmax, N;
488: PetscInt *imax = a->imax, *ai = a->i, *ailen = a->ilen;
489: PetscInt *aj = a->j, nonew = a->nonew, bs2 = a->bs2, bs = A->rmap->bs;
490: PetscBool roworiented = a->roworiented;
491: const PetscScalar *value = v;
492: MatScalar *ap, *aa = a->a, *bap;
494: PetscFunctionBegin;
495: rp = aj + ai[row];
496: ap = aa + bs2 * ai[row];
497: rmax = imax[row];
498: nrow = ailen[row];
499: low = 0;
500: high = nrow;
501: value = v;
502: while (high - low > 7) {
503: t = (low + high) / 2;
504: if (rp[t] > col) high = t;
505: else low = t;
506: }
507: for (i = low; i < high; i++) {
508: if (rp[i] > col) break;
509: if (rp[i] == col) {
510: bap = ap + bs2 * i;
511: if (roworiented) {
512: if (is == ADD_VALUES) {
513: for (ii = 0; ii < bs; ii++) {
514: for (jj = ii; jj < bs2; jj += bs) bap[jj] += *value++;
515: }
516: } else {
517: for (ii = 0; ii < bs; ii++) {
518: for (jj = ii; jj < bs2; jj += bs) bap[jj] = *value++;
519: }
520: }
521: } else {
522: if (is == ADD_VALUES) {
523: for (ii = 0; ii < bs; ii++, value += bs) {
524: for (jj = 0; jj < bs; jj++) bap[jj] += value[jj];
525: bap += bs;
526: }
527: } else {
528: for (ii = 0; ii < bs; ii++, value += bs) {
529: for (jj = 0; jj < bs; jj++) bap[jj] = value[jj];
530: bap += bs;
531: }
532: }
533: }
534: goto noinsert2;
535: }
536: }
537: if (nonew == 1) goto noinsert2;
538: PetscCheck(nonew != -1, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Inserting a new global block indexed nonzero block (%" PetscInt_FMT ", %" PetscInt_FMT ") in the matrix", orow, ocol);
539: MatSeqXAIJReallocateAIJ(A, a->mbs, bs2, nrow, row, col, rmax, aa, ai, aj, rp, ap, imax, nonew, MatScalar);
540: N = nrow++ - 1;
541: high++;
542: /* shift up all the later entries in this row */
543: PetscCall(PetscArraymove(rp + i + 1, rp + i, N - i + 1));
544: PetscCall(PetscArraymove(ap + bs2 * (i + 1), ap + bs2 * i, bs2 * (N - i + 1)));
545: rp[i] = col;
546: bap = ap + bs2 * i;
547: if (roworiented) {
548: for (ii = 0; ii < bs; ii++) {
549: for (jj = ii; jj < bs2; jj += bs) bap[jj] = *value++;
550: }
551: } else {
552: for (ii = 0; ii < bs; ii++) {
553: for (jj = 0; jj < bs; jj++) *bap++ = *value++;
554: }
555: }
556: noinsert2:;
557: ailen[row] = nrow;
558: PetscFunctionReturn(PETSC_SUCCESS);
559: }
561: /*
562: This routine could be optimized by removing the need for the block copy below and passing stride information
563: to the above inline routines; similarly in MatSetValuesBlocked_MPIBAIJ()
564: */
565: static PetscErrorCode MatSetValuesBlocked_MPISBAIJ(Mat mat, PetscInt m, const PetscInt im[], PetscInt n, const PetscInt in[], const MatScalar v[], InsertMode addv)
566: {
567: Mat_MPISBAIJ *baij = (Mat_MPISBAIJ *)mat->data;
568: const MatScalar *value;
569: MatScalar *barray = baij->barray;
570: PetscBool roworiented = baij->roworiented, ignore_ltriangular = ((Mat_SeqSBAIJ *)baij->A->data)->ignore_ltriangular;
571: PetscInt i, j, ii, jj, row, col, rstart = baij->rstartbs;
572: PetscInt rend = baij->rendbs, cstart = baij->cstartbs, stepval;
573: PetscInt cend = baij->cendbs, bs = mat->rmap->bs, bs2 = baij->bs2;
575: PetscFunctionBegin;
576: if (!barray) {
577: PetscCall(PetscMalloc1(bs2, &barray));
578: baij->barray = barray;
579: }
581: if (roworiented) {
582: stepval = (n - 1) * bs;
583: } else {
584: stepval = (m - 1) * bs;
585: }
586: for (i = 0; i < m; i++) {
587: if (im[i] < 0) continue;
588: PetscCheck(im[i] < baij->Mbs, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Block indexed row too large %" PetscInt_FMT " max %" PetscInt_FMT, im[i], baij->Mbs - 1);
589: if (im[i] >= rstart && im[i] < rend) {
590: row = im[i] - rstart;
591: for (j = 0; j < n; j++) {
592: if (im[i] > in[j]) {
593: if (ignore_ltriangular) continue; /* ignore lower triangular blocks */
594: else SETERRQ(PETSC_COMM_SELF, PETSC_ERR_USER, "Lower triangular value cannot be set for sbaij format. Ignoring these values, run with -mat_ignore_lower_triangular or call MatSetOption(mat,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE)");
595: }
596: /* If NumCol = 1 then a copy is not required */
597: if ((roworiented) && (n == 1)) {
598: barray = (MatScalar *)v + i * bs2;
599: } else if ((!roworiented) && (m == 1)) {
600: barray = (MatScalar *)v + j * bs2;
601: } else { /* Here a copy is required */
602: if (roworiented) {
603: value = v + i * (stepval + bs) * bs + j * bs;
604: } else {
605: value = v + j * (stepval + bs) * bs + i * bs;
606: }
607: for (ii = 0; ii < bs; ii++, value += stepval) {
608: for (jj = 0; jj < bs; jj++) *barray++ = *value++;
609: }
610: barray -= bs2;
611: }
613: if (in[j] >= cstart && in[j] < cend) {
614: col = in[j] - cstart;
615: PetscCall(MatSetValuesBlocked_SeqSBAIJ_Inlined(baij->A, row, col, barray, addv, im[i], in[j]));
616: } else if (in[j] < 0) {
617: continue;
618: } else {
619: PetscCheck(in[j] < baij->Nbs, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Block indexed column too large %" PetscInt_FMT " max %" PetscInt_FMT, in[j], baij->Nbs - 1);
620: if (mat->was_assembled) {
621: if (!baij->colmap) PetscCall(MatCreateColmap_MPIBAIJ_Private(mat));
623: #if defined(PETSC_USE_CTABLE)
624: PetscCall(PetscHMapIGetWithDefault(baij->colmap, in[j] + 1, 0, &col));
625: col = col < 1 ? -1 : (col - 1) / bs;
626: #else
627: col = baij->colmap[in[j]] < 1 ? -1 : (baij->colmap[in[j]] - 1) / bs;
628: #endif
629: if (col < 0 && !((Mat_SeqBAIJ *)baij->A->data)->nonew) {
630: PetscCall(MatDisAssemble_MPISBAIJ(mat));
631: col = in[j];
632: }
633: } else col = in[j];
634: PetscCall(MatSetValuesBlocked_SeqBAIJ_Inlined(baij->B, row, col, barray, addv, im[i], in[j]));
635: }
636: }
637: } else {
638: PetscCheck(!mat->nooffprocentries, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Setting off process block indexed row %" PetscInt_FMT " even though MatSetOption(,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) was set", im[i]);
639: if (!baij->donotstash) {
640: if (roworiented) {
641: PetscCall(MatStashValuesRowBlocked_Private(&mat->bstash, im[i], n, in, v, m, n, i));
642: } else {
643: PetscCall(MatStashValuesColBlocked_Private(&mat->bstash, im[i], n, in, v, m, n, i));
644: }
645: }
646: }
647: }
648: PetscFunctionReturn(PETSC_SUCCESS);
649: }
651: static PetscErrorCode MatGetValues_MPISBAIJ(Mat mat, PetscInt m, const PetscInt idxm[], PetscInt n, const PetscInt idxn[], PetscScalar v[])
652: {
653: Mat_MPISBAIJ *baij = (Mat_MPISBAIJ *)mat->data;
654: PetscInt bs = mat->rmap->bs, i, j, bsrstart = mat->rmap->rstart, bsrend = mat->rmap->rend;
655: PetscInt bscstart = mat->cmap->rstart, bscend = mat->cmap->rend, row, col, data;
657: PetscFunctionBegin;
658: for (i = 0; i < m; i++) {
659: if (idxm[i] < 0) continue; /* negative row */
660: PetscCheck(idxm[i] < mat->rmap->N, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Row too large: row %" PetscInt_FMT " max %" PetscInt_FMT, idxm[i], mat->rmap->N - 1);
661: if (idxm[i] >= bsrstart && idxm[i] < bsrend) {
662: row = idxm[i] - bsrstart;
663: for (j = 0; j < n; j++) {
664: if (idxn[j] < 0) continue; /* negative column */
665: PetscCheck(idxn[j] < mat->cmap->N, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Column too large: col %" PetscInt_FMT " max %" PetscInt_FMT, idxn[j], mat->cmap->N - 1);
666: if (idxn[j] >= bscstart && idxn[j] < bscend) {
667: col = idxn[j] - bscstart;
668: PetscCall(MatGetValues_SeqSBAIJ(baij->A, 1, &row, 1, &col, v + i * n + j));
669: } else {
670: if (!baij->colmap) PetscCall(MatCreateColmap_MPIBAIJ_Private(mat));
671: #if defined(PETSC_USE_CTABLE)
672: PetscCall(PetscHMapIGetWithDefault(baij->colmap, idxn[j] / bs + 1, 0, &data));
673: data--;
674: #else
675: data = baij->colmap[idxn[j] / bs] - 1;
676: #endif
677: if ((data < 0) || (baij->garray[data / bs] != idxn[j] / bs)) *(v + i * n + j) = 0.0;
678: else {
679: col = data + idxn[j] % bs;
680: PetscCall(MatGetValues_SeqBAIJ(baij->B, 1, &row, 1, &col, v + i * n + j));
681: }
682: }
683: }
684: } else SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP, "Only local values currently supported");
685: }
686: PetscFunctionReturn(PETSC_SUCCESS);
687: }
689: static PetscErrorCode MatNorm_MPISBAIJ(Mat mat, NormType type, PetscReal *norm)
690: {
691: Mat_MPISBAIJ *baij = (Mat_MPISBAIJ *)mat->data;
692: PetscReal sum[2], *lnorm2;
694: PetscFunctionBegin;
695: if (baij->size == 1) {
696: PetscCall(MatNorm(baij->A, type, norm));
697: } else {
698: if (type == NORM_FROBENIUS) {
699: PetscCall(PetscMalloc1(2, &lnorm2));
700: PetscCall(MatNorm(baij->A, type, lnorm2));
701: *lnorm2 = (*lnorm2) * (*lnorm2);
702: lnorm2++; /* squar power of norm(A) */
703: PetscCall(MatNorm(baij->B, type, lnorm2));
704: *lnorm2 = (*lnorm2) * (*lnorm2);
705: lnorm2--; /* squar power of norm(B) */
706: PetscCallMPI(MPIU_Allreduce(lnorm2, sum, 2, MPIU_REAL, MPIU_SUM, PetscObjectComm((PetscObject)mat)));
707: *norm = PetscSqrtReal(sum[0] + 2 * sum[1]);
708: PetscCall(PetscFree(lnorm2));
709: } else if (type == NORM_INFINITY || type == NORM_1) { /* max row/column sum */
710: Mat_SeqSBAIJ *amat = (Mat_SeqSBAIJ *)baij->A->data;
711: Mat_SeqBAIJ *bmat = (Mat_SeqBAIJ *)baij->B->data;
712: PetscReal *rsum, vabs;
713: PetscInt *jj, *garray = baij->garray, rstart = baij->rstartbs, nz;
714: PetscInt brow, bcol, col, bs = baij->A->rmap->bs, row, grow, gcol, mbs = amat->mbs;
715: MatScalar *v;
717: PetscCall(PetscMalloc1(mat->cmap->N, &rsum));
718: PetscCall(PetscArrayzero(rsum, mat->cmap->N));
719: /* Amat */
720: v = amat->a;
721: jj = amat->j;
722: for (brow = 0; brow < mbs; brow++) {
723: grow = bs * (rstart + brow);
724: nz = amat->i[brow + 1] - amat->i[brow];
725: for (bcol = 0; bcol < nz; bcol++) {
726: gcol = bs * (rstart + *jj);
727: jj++;
728: for (col = 0; col < bs; col++) {
729: for (row = 0; row < bs; row++) {
730: vabs = PetscAbsScalar(*v);
731: v++;
732: rsum[gcol + col] += vabs;
733: /* non-diagonal block */
734: if (bcol > 0 && vabs > 0.0) rsum[grow + row] += vabs;
735: }
736: }
737: }
738: PetscCall(PetscLogFlops(nz * bs * bs));
739: }
740: /* Bmat */
741: v = bmat->a;
742: jj = bmat->j;
743: for (brow = 0; brow < mbs; brow++) {
744: grow = bs * (rstart + brow);
745: nz = bmat->i[brow + 1] - bmat->i[brow];
746: for (bcol = 0; bcol < nz; bcol++) {
747: gcol = bs * garray[*jj];
748: jj++;
749: for (col = 0; col < bs; col++) {
750: for (row = 0; row < bs; row++) {
751: vabs = PetscAbsScalar(*v);
752: v++;
753: rsum[gcol + col] += vabs;
754: rsum[grow + row] += vabs;
755: }
756: }
757: }
758: PetscCall(PetscLogFlops(nz * bs * bs));
759: }
760: PetscCallMPI(MPIU_Allreduce(MPI_IN_PLACE, rsum, mat->cmap->N, MPIU_REAL, MPIU_SUM, PetscObjectComm((PetscObject)mat)));
761: *norm = 0.0;
762: for (col = 0; col < mat->cmap->N; col++) {
763: if (rsum[col] > *norm) *norm = rsum[col];
764: }
765: PetscCall(PetscFree(rsum));
766: } else SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP, "No support for this norm yet");
767: }
768: PetscFunctionReturn(PETSC_SUCCESS);
769: }
771: static PetscErrorCode MatAssemblyBegin_MPISBAIJ(Mat mat, MatAssemblyType mode)
772: {
773: Mat_MPISBAIJ *baij = (Mat_MPISBAIJ *)mat->data;
774: PetscInt nstash, reallocs;
776: PetscFunctionBegin;
777: if (baij->donotstash || mat->nooffprocentries) PetscFunctionReturn(PETSC_SUCCESS);
779: PetscCall(MatStashScatterBegin_Private(mat, &mat->stash, mat->rmap->range));
780: PetscCall(MatStashScatterBegin_Private(mat, &mat->bstash, baij->rangebs));
781: PetscCall(MatStashGetInfo_Private(&mat->stash, &nstash, &reallocs));
782: PetscCall(PetscInfo(mat, "Stash has %" PetscInt_FMT " entries,uses %" PetscInt_FMT " mallocs.\n", nstash, reallocs));
783: PetscCall(MatStashGetInfo_Private(&mat->stash, &nstash, &reallocs));
784: PetscCall(PetscInfo(mat, "Block-Stash has %" PetscInt_FMT " entries, uses %" PetscInt_FMT " mallocs.\n", nstash, reallocs));
785: PetscFunctionReturn(PETSC_SUCCESS);
786: }
788: static PetscErrorCode MatAssemblyEnd_MPISBAIJ(Mat mat, MatAssemblyType mode)
789: {
790: Mat_MPISBAIJ *baij = (Mat_MPISBAIJ *)mat->data;
791: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)baij->A->data;
792: PetscInt i, j, rstart, ncols, flg, bs2 = baij->bs2;
793: PetscInt *row, *col;
794: PetscBool other_disassembled;
795: PetscMPIInt n;
796: PetscBool r1, r2, r3;
797: MatScalar *val;
799: /* do not use 'b=(Mat_SeqBAIJ*)baij->B->data' as B can be reset in disassembly */
800: PetscFunctionBegin;
801: if (!baij->donotstash && !mat->nooffprocentries) {
802: while (1) {
803: PetscCall(MatStashScatterGetMesg_Private(&mat->stash, &n, &row, &col, &val, &flg));
804: if (!flg) break;
806: for (i = 0; i < n;) {
807: /* Now identify the consecutive vals belonging to the same row */
808: for (j = i, rstart = row[j]; j < n; j++) {
809: if (row[j] != rstart) break;
810: }
811: if (j < n) ncols = j - i;
812: else ncols = n - i;
813: /* Now assemble all these values with a single function call */
814: PetscCall(MatSetValues_MPISBAIJ(mat, 1, row + i, ncols, col + i, val + i, mat->insertmode));
815: i = j;
816: }
817: }
818: PetscCall(MatStashScatterEnd_Private(&mat->stash));
819: /* Now process the block-stash. Since the values are stashed column-oriented,
820: set the row-oriented flag to column-oriented, and after MatSetValues()
821: restore the original flags */
822: r1 = baij->roworiented;
823: r2 = a->roworiented;
824: r3 = ((Mat_SeqBAIJ *)baij->B->data)->roworiented;
826: baij->roworiented = PETSC_FALSE;
827: a->roworiented = PETSC_FALSE;
829: ((Mat_SeqBAIJ *)baij->B->data)->roworiented = PETSC_FALSE; /* b->roworinted */
830: while (1) {
831: PetscCall(MatStashScatterGetMesg_Private(&mat->bstash, &n, &row, &col, &val, &flg));
832: if (!flg) break;
834: for (i = 0; i < n;) {
835: /* Now identify the consecutive vals belonging to the same row */
836: for (j = i, rstart = row[j]; j < n; j++) {
837: if (row[j] != rstart) break;
838: }
839: if (j < n) ncols = j - i;
840: else ncols = n - i;
841: PetscCall(MatSetValuesBlocked_MPISBAIJ(mat, 1, row + i, ncols, col + i, val + i * bs2, mat->insertmode));
842: i = j;
843: }
844: }
845: PetscCall(MatStashScatterEnd_Private(&mat->bstash));
847: baij->roworiented = r1;
848: a->roworiented = r2;
850: ((Mat_SeqBAIJ *)baij->B->data)->roworiented = r3; /* b->roworinted */
851: }
853: PetscCall(MatAssemblyBegin(baij->A, mode));
854: PetscCall(MatAssemblyEnd(baij->A, mode));
856: /* determine if any processor has disassembled, if so we must
857: also disassemble ourselves, in order that we may reassemble. */
858: /*
859: if nonzero structure of submatrix B cannot change then we know that
860: no processor disassembled thus we can skip this stuff
861: */
862: if (!((Mat_SeqBAIJ *)baij->B->data)->nonew) {
863: PetscCallMPI(MPIU_Allreduce(&mat->was_assembled, &other_disassembled, 1, MPIU_BOOL, MPI_LAND, PetscObjectComm((PetscObject)mat)));
864: if (mat->was_assembled && !other_disassembled) PetscCall(MatDisAssemble_MPISBAIJ(mat));
865: }
867: if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { PetscCall(MatSetUpMultiply_MPISBAIJ(mat)); /* setup Mvctx and sMvctx */ }
868: PetscCall(MatAssemblyBegin(baij->B, mode));
869: PetscCall(MatAssemblyEnd(baij->B, mode));
871: PetscCall(PetscFree2(baij->rowvalues, baij->rowindices));
873: baij->rowvalues = NULL;
875: /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */
876: if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqBAIJ *)baij->A->data)->nonew) {
877: PetscObjectState state = baij->A->nonzerostate + baij->B->nonzerostate;
878: PetscCallMPI(MPIU_Allreduce(&state, &mat->nonzerostate, 1, MPIU_INT64, MPI_SUM, PetscObjectComm((PetscObject)mat)));
879: }
880: PetscFunctionReturn(PETSC_SUCCESS);
881: }
883: extern PetscErrorCode MatSetValues_MPIBAIJ(Mat, PetscInt, const PetscInt[], PetscInt, const PetscInt[], const PetscScalar[], InsertMode);
884: #include <petscdraw.h>
885: static PetscErrorCode MatView_MPISBAIJ_ASCIIorDraworSocket(Mat mat, PetscViewer viewer)
886: {
887: Mat_MPISBAIJ *baij = (Mat_MPISBAIJ *)mat->data;
888: PetscInt bs = mat->rmap->bs;
889: PetscMPIInt rank = baij->rank;
890: PetscBool iascii, isdraw;
891: PetscViewer sviewer;
892: PetscViewerFormat format;
894: PetscFunctionBegin;
895: PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERASCII, &iascii));
896: PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERDRAW, &isdraw));
897: if (iascii) {
898: PetscCall(PetscViewerGetFormat(viewer, &format));
899: if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
900: MatInfo info;
901: PetscCallMPI(MPI_Comm_rank(PetscObjectComm((PetscObject)mat), &rank));
902: PetscCall(MatGetInfo(mat, MAT_LOCAL, &info));
903: PetscCall(PetscViewerASCIIPushSynchronized(viewer));
904: PetscCall(PetscViewerASCIISynchronizedPrintf(viewer, "[%d] Local rows %" PetscInt_FMT " nz %" PetscInt_FMT " nz alloced %" PetscInt_FMT " bs %" PetscInt_FMT " mem %g\n", rank, mat->rmap->n, (PetscInt)info.nz_used, (PetscInt)info.nz_allocated,
905: mat->rmap->bs, info.memory));
906: PetscCall(MatGetInfo(baij->A, MAT_LOCAL, &info));
907: PetscCall(PetscViewerASCIISynchronizedPrintf(viewer, "[%d] on-diagonal part: nz %" PetscInt_FMT " \n", rank, (PetscInt)info.nz_used));
908: PetscCall(MatGetInfo(baij->B, MAT_LOCAL, &info));
909: PetscCall(PetscViewerASCIISynchronizedPrintf(viewer, "[%d] off-diagonal part: nz %" PetscInt_FMT " \n", rank, (PetscInt)info.nz_used));
910: PetscCall(PetscViewerFlush(viewer));
911: PetscCall(PetscViewerASCIIPopSynchronized(viewer));
912: PetscCall(PetscViewerASCIIPrintf(viewer, "Information on VecScatter used in matrix-vector product: \n"));
913: PetscCall(VecScatterView(baij->Mvctx, viewer));
914: PetscFunctionReturn(PETSC_SUCCESS);
915: } else if (format == PETSC_VIEWER_ASCII_INFO) {
916: PetscCall(PetscViewerASCIIPrintf(viewer, " block size is %" PetscInt_FMT "\n", bs));
917: PetscFunctionReturn(PETSC_SUCCESS);
918: } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
919: PetscFunctionReturn(PETSC_SUCCESS);
920: }
921: }
923: if (isdraw) {
924: PetscDraw draw;
925: PetscBool isnull;
926: PetscCall(PetscViewerDrawGetDraw(viewer, 0, &draw));
927: PetscCall(PetscDrawIsNull(draw, &isnull));
928: if (isnull) PetscFunctionReturn(PETSC_SUCCESS);
929: }
931: {
932: /* assemble the entire matrix onto first processor. */
933: Mat A;
934: Mat_SeqSBAIJ *Aloc;
935: Mat_SeqBAIJ *Bloc;
936: PetscInt M = mat->rmap->N, N = mat->cmap->N, *ai, *aj, col, i, j, k, *rvals, mbs = baij->mbs;
937: MatScalar *a;
938: const char *matname;
940: /* Should this be the same type as mat? */
941: PetscCall(MatCreate(PetscObjectComm((PetscObject)mat), &A));
942: if (rank == 0) {
943: PetscCall(MatSetSizes(A, M, N, M, N));
944: } else {
945: PetscCall(MatSetSizes(A, 0, 0, M, N));
946: }
947: PetscCall(MatSetType(A, MATMPISBAIJ));
948: PetscCall(MatMPISBAIJSetPreallocation(A, mat->rmap->bs, 0, NULL, 0, NULL));
949: PetscCall(MatSetOption(A, MAT_NEW_NONZERO_LOCATION_ERR, PETSC_FALSE));
951: /* copy over the A part */
952: Aloc = (Mat_SeqSBAIJ *)baij->A->data;
953: ai = Aloc->i;
954: aj = Aloc->j;
955: a = Aloc->a;
956: PetscCall(PetscMalloc1(bs, &rvals));
958: for (i = 0; i < mbs; i++) {
959: rvals[0] = bs * (baij->rstartbs + i);
960: for (j = 1; j < bs; j++) rvals[j] = rvals[j - 1] + 1;
961: for (j = ai[i]; j < ai[i + 1]; j++) {
962: col = (baij->cstartbs + aj[j]) * bs;
963: for (k = 0; k < bs; k++) {
964: PetscCall(MatSetValues_MPISBAIJ(A, bs, rvals, 1, &col, a, INSERT_VALUES));
965: col++;
966: a += bs;
967: }
968: }
969: }
970: /* copy over the B part */
971: Bloc = (Mat_SeqBAIJ *)baij->B->data;
972: ai = Bloc->i;
973: aj = Bloc->j;
974: a = Bloc->a;
975: for (i = 0; i < mbs; i++) {
976: rvals[0] = bs * (baij->rstartbs + i);
977: for (j = 1; j < bs; j++) rvals[j] = rvals[j - 1] + 1;
978: for (j = ai[i]; j < ai[i + 1]; j++) {
979: col = baij->garray[aj[j]] * bs;
980: for (k = 0; k < bs; k++) {
981: PetscCall(MatSetValues_MPIBAIJ(A, bs, rvals, 1, &col, a, INSERT_VALUES));
982: col++;
983: a += bs;
984: }
985: }
986: }
987: PetscCall(PetscFree(rvals));
988: PetscCall(MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY));
989: PetscCall(MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY));
990: /*
991: Everyone has to call to draw the matrix since the graphics waits are
992: synchronized across all processors that share the PetscDraw object
993: */
994: PetscCall(PetscViewerGetSubViewer(viewer, PETSC_COMM_SELF, &sviewer));
995: if (((PetscObject)mat)->name) PetscCall(PetscObjectGetName((PetscObject)mat, &matname));
996: if (rank == 0) {
997: if (((PetscObject)mat)->name) PetscCall(PetscObjectSetName((PetscObject)((Mat_MPISBAIJ *)A->data)->A, matname));
998: PetscCall(MatView_SeqSBAIJ(((Mat_MPISBAIJ *)A->data)->A, sviewer));
999: }
1000: PetscCall(PetscViewerRestoreSubViewer(viewer, PETSC_COMM_SELF, &sviewer));
1001: PetscCall(MatDestroy(&A));
1002: }
1003: PetscFunctionReturn(PETSC_SUCCESS);
1004: }
1006: /* Used for both MPIBAIJ and MPISBAIJ matrices */
1007: #define MatView_MPISBAIJ_Binary MatView_MPIBAIJ_Binary
1009: static PetscErrorCode MatView_MPISBAIJ(Mat mat, PetscViewer viewer)
1010: {
1011: PetscBool iascii, isdraw, issocket, isbinary;
1013: PetscFunctionBegin;
1014: PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERASCII, &iascii));
1015: PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERDRAW, &isdraw));
1016: PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERSOCKET, &issocket));
1017: PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERBINARY, &isbinary));
1018: if (iascii || isdraw || issocket) {
1019: PetscCall(MatView_MPISBAIJ_ASCIIorDraworSocket(mat, viewer));
1020: } else if (isbinary) PetscCall(MatView_MPISBAIJ_Binary(mat, viewer));
1021: PetscFunctionReturn(PETSC_SUCCESS);
1022: }
1024: #if defined(PETSC_USE_COMPLEX)
1025: static PetscErrorCode MatMult_MPISBAIJ_Hermitian(Mat A, Vec xx, Vec yy)
1026: {
1027: Mat_MPISBAIJ *a = (Mat_MPISBAIJ *)A->data;
1028: PetscInt mbs = a->mbs, bs = A->rmap->bs;
1029: PetscScalar *from;
1030: const PetscScalar *x;
1032: PetscFunctionBegin;
1033: /* diagonal part */
1034: PetscCall((*a->A->ops->mult)(a->A, xx, a->slvec1a));
1035: /* since a->slvec1b shares memory (dangerously) with a->slec1 changes to a->slec1 will affect it */
1036: PetscCall(PetscObjectStateIncrease((PetscObject)a->slvec1b));
1037: PetscCall(VecZeroEntries(a->slvec1b));
1039: /* subdiagonal part */
1040: PetscCheck(a->B->ops->multhermitiantranspose, PetscObjectComm((PetscObject)a->B), PETSC_ERR_SUP, "Not for type %s", ((PetscObject)a->B)->type_name);
1041: PetscCall((*a->B->ops->multhermitiantranspose)(a->B, xx, a->slvec0b));
1043: /* copy x into the vec slvec0 */
1044: PetscCall(VecGetArray(a->slvec0, &from));
1045: PetscCall(VecGetArrayRead(xx, &x));
1047: PetscCall(PetscArraycpy(from, x, bs * mbs));
1048: PetscCall(VecRestoreArray(a->slvec0, &from));
1049: PetscCall(VecRestoreArrayRead(xx, &x));
1051: PetscCall(VecScatterBegin(a->sMvctx, a->slvec0, a->slvec1, ADD_VALUES, SCATTER_FORWARD));
1052: PetscCall(VecScatterEnd(a->sMvctx, a->slvec0, a->slvec1, ADD_VALUES, SCATTER_FORWARD));
1053: /* supperdiagonal part */
1054: PetscCall((*a->B->ops->multadd)(a->B, a->slvec1b, a->slvec1a, yy));
1055: PetscFunctionReturn(PETSC_SUCCESS);
1056: }
1057: #endif
1059: static PetscErrorCode MatMult_MPISBAIJ(Mat A, Vec xx, Vec yy)
1060: {
1061: Mat_MPISBAIJ *a = (Mat_MPISBAIJ *)A->data;
1062: PetscInt mbs = a->mbs, bs = A->rmap->bs;
1063: PetscScalar *from;
1064: const PetscScalar *x;
1066: PetscFunctionBegin;
1067: /* diagonal part */
1068: PetscCall((*a->A->ops->mult)(a->A, xx, a->slvec1a));
1069: /* since a->slvec1b shares memory (dangerously) with a->slec1 changes to a->slec1 will affect it */
1070: PetscCall(PetscObjectStateIncrease((PetscObject)a->slvec1b));
1071: PetscCall(VecZeroEntries(a->slvec1b));
1073: /* subdiagonal part */
1074: PetscCall((*a->B->ops->multtranspose)(a->B, xx, a->slvec0b));
1076: /* copy x into the vec slvec0 */
1077: PetscCall(VecGetArray(a->slvec0, &from));
1078: PetscCall(VecGetArrayRead(xx, &x));
1080: PetscCall(PetscArraycpy(from, x, bs * mbs));
1081: PetscCall(VecRestoreArray(a->slvec0, &from));
1082: PetscCall(VecRestoreArrayRead(xx, &x));
1084: PetscCall(VecScatterBegin(a->sMvctx, a->slvec0, a->slvec1, ADD_VALUES, SCATTER_FORWARD));
1085: PetscCall(VecScatterEnd(a->sMvctx, a->slvec0, a->slvec1, ADD_VALUES, SCATTER_FORWARD));
1086: /* supperdiagonal part */
1087: PetscCall((*a->B->ops->multadd)(a->B, a->slvec1b, a->slvec1a, yy));
1088: PetscFunctionReturn(PETSC_SUCCESS);
1089: }
1091: #if PetscDefined(USE_COMPLEX)
1092: static PetscErrorCode MatMultAdd_MPISBAIJ_Hermitian(Mat A, Vec xx, Vec yy, Vec zz)
1093: {
1094: Mat_MPISBAIJ *a = (Mat_MPISBAIJ *)A->data;
1095: PetscInt mbs = a->mbs, bs = A->rmap->bs;
1096: PetscScalar *from;
1097: const PetscScalar *x;
1099: PetscFunctionBegin;
1100: /* diagonal part */
1101: PetscCall((*a->A->ops->multadd)(a->A, xx, yy, a->slvec1a));
1102: PetscCall(PetscObjectStateIncrease((PetscObject)a->slvec1b));
1103: PetscCall(VecZeroEntries(a->slvec1b));
1105: /* subdiagonal part */
1106: PetscCheck(a->B->ops->multhermitiantranspose, PetscObjectComm((PetscObject)a->B), PETSC_ERR_SUP, "Not for type %s", ((PetscObject)a->B)->type_name);
1107: PetscCall((*a->B->ops->multhermitiantranspose)(a->B, xx, a->slvec0b));
1109: /* copy x into the vec slvec0 */
1110: PetscCall(VecGetArray(a->slvec0, &from));
1111: PetscCall(VecGetArrayRead(xx, &x));
1112: PetscCall(PetscArraycpy(from, x, bs * mbs));
1113: PetscCall(VecRestoreArray(a->slvec0, &from));
1115: PetscCall(VecScatterBegin(a->sMvctx, a->slvec0, a->slvec1, ADD_VALUES, SCATTER_FORWARD));
1116: PetscCall(VecRestoreArrayRead(xx, &x));
1117: PetscCall(VecScatterEnd(a->sMvctx, a->slvec0, a->slvec1, ADD_VALUES, SCATTER_FORWARD));
1119: /* supperdiagonal part */
1120: PetscCall((*a->B->ops->multadd)(a->B, a->slvec1b, a->slvec1a, zz));
1121: PetscFunctionReturn(PETSC_SUCCESS);
1122: }
1123: #endif
1125: static PetscErrorCode MatMultAdd_MPISBAIJ(Mat A, Vec xx, Vec yy, Vec zz)
1126: {
1127: Mat_MPISBAIJ *a = (Mat_MPISBAIJ *)A->data;
1128: PetscInt mbs = a->mbs, bs = A->rmap->bs;
1129: PetscScalar *from;
1130: const PetscScalar *x;
1132: PetscFunctionBegin;
1133: /* diagonal part */
1134: PetscCall((*a->A->ops->multadd)(a->A, xx, yy, a->slvec1a));
1135: PetscCall(PetscObjectStateIncrease((PetscObject)a->slvec1b));
1136: PetscCall(VecZeroEntries(a->slvec1b));
1138: /* subdiagonal part */
1139: PetscCall((*a->B->ops->multtranspose)(a->B, xx, a->slvec0b));
1141: /* copy x into the vec slvec0 */
1142: PetscCall(VecGetArray(a->slvec0, &from));
1143: PetscCall(VecGetArrayRead(xx, &x));
1144: PetscCall(PetscArraycpy(from, x, bs * mbs));
1145: PetscCall(VecRestoreArray(a->slvec0, &from));
1147: PetscCall(VecScatterBegin(a->sMvctx, a->slvec0, a->slvec1, ADD_VALUES, SCATTER_FORWARD));
1148: PetscCall(VecRestoreArrayRead(xx, &x));
1149: PetscCall(VecScatterEnd(a->sMvctx, a->slvec0, a->slvec1, ADD_VALUES, SCATTER_FORWARD));
1151: /* supperdiagonal part */
1152: PetscCall((*a->B->ops->multadd)(a->B, a->slvec1b, a->slvec1a, zz));
1153: PetscFunctionReturn(PETSC_SUCCESS);
1154: }
1156: /*
1157: This only works correctly for square matrices where the subblock A->A is the
1158: diagonal block
1159: */
1160: static PetscErrorCode MatGetDiagonal_MPISBAIJ(Mat A, Vec v)
1161: {
1162: Mat_MPISBAIJ *a = (Mat_MPISBAIJ *)A->data;
1164: PetscFunctionBegin;
1165: /* PetscCheck(a->rmap->N == a->cmap->N,PETSC_COMM_SELF,PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); */
1166: PetscCall(MatGetDiagonal(a->A, v));
1167: PetscFunctionReturn(PETSC_SUCCESS);
1168: }
1170: static PetscErrorCode MatScale_MPISBAIJ(Mat A, PetscScalar aa)
1171: {
1172: Mat_MPISBAIJ *a = (Mat_MPISBAIJ *)A->data;
1174: PetscFunctionBegin;
1175: PetscCall(MatScale(a->A, aa));
1176: PetscCall(MatScale(a->B, aa));
1177: PetscFunctionReturn(PETSC_SUCCESS);
1178: }
1180: static PetscErrorCode MatGetRow_MPISBAIJ(Mat matin, PetscInt row, PetscInt *nz, PetscInt **idx, PetscScalar **v)
1181: {
1182: Mat_MPISBAIJ *mat = (Mat_MPISBAIJ *)matin->data;
1183: PetscScalar *vworkA, *vworkB, **pvA, **pvB, *v_p;
1184: PetscInt bs = matin->rmap->bs, bs2 = mat->bs2, i, *cworkA, *cworkB, **pcA, **pcB;
1185: PetscInt nztot, nzA, nzB, lrow, brstart = matin->rmap->rstart, brend = matin->rmap->rend;
1186: PetscInt *cmap, *idx_p, cstart = mat->rstartbs;
1188: PetscFunctionBegin;
1189: PetscCheck(!mat->getrowactive, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONGSTATE, "Already active");
1190: mat->getrowactive = PETSC_TRUE;
1192: if (!mat->rowvalues && (idx || v)) {
1193: /*
1194: allocate enough space to hold information from the longest row.
1195: */
1196: Mat_SeqSBAIJ *Aa = (Mat_SeqSBAIJ *)mat->A->data;
1197: Mat_SeqBAIJ *Ba = (Mat_SeqBAIJ *)mat->B->data;
1198: PetscInt max = 1, mbs = mat->mbs, tmp;
1199: for (i = 0; i < mbs; i++) {
1200: tmp = Aa->i[i + 1] - Aa->i[i] + Ba->i[i + 1] - Ba->i[i]; /* row length */
1201: if (max < tmp) max = tmp;
1202: }
1203: PetscCall(PetscMalloc2(max * bs2, &mat->rowvalues, max * bs2, &mat->rowindices));
1204: }
1206: PetscCheck(row >= brstart && row < brend, PETSC_COMM_SELF, PETSC_ERR_SUP, "Only local rows");
1207: lrow = row - brstart; /* local row index */
1209: pvA = &vworkA;
1210: pcA = &cworkA;
1211: pvB = &vworkB;
1212: pcB = &cworkB;
1213: if (!v) {
1214: pvA = NULL;
1215: pvB = NULL;
1216: }
1217: if (!idx) {
1218: pcA = NULL;
1219: if (!v) pcB = NULL;
1220: }
1221: PetscCall((*mat->A->ops->getrow)(mat->A, lrow, &nzA, pcA, pvA));
1222: PetscCall((*mat->B->ops->getrow)(mat->B, lrow, &nzB, pcB, pvB));
1223: nztot = nzA + nzB;
1225: cmap = mat->garray;
1226: if (v || idx) {
1227: if (nztot) {
1228: /* Sort by increasing column numbers, assuming A and B already sorted */
1229: PetscInt imark = -1;
1230: if (v) {
1231: *v = v_p = mat->rowvalues;
1232: for (i = 0; i < nzB; i++) {
1233: if (cmap[cworkB[i] / bs] < cstart) v_p[i] = vworkB[i];
1234: else break;
1235: }
1236: imark = i;
1237: for (i = 0; i < nzA; i++) v_p[imark + i] = vworkA[i];
1238: for (i = imark; i < nzB; i++) v_p[nzA + i] = vworkB[i];
1239: }
1240: if (idx) {
1241: *idx = idx_p = mat->rowindices;
1242: if (imark > -1) {
1243: for (i = 0; i < imark; i++) idx_p[i] = cmap[cworkB[i] / bs] * bs + cworkB[i] % bs;
1244: } else {
1245: for (i = 0; i < nzB; i++) {
1246: if (cmap[cworkB[i] / bs] < cstart) idx_p[i] = cmap[cworkB[i] / bs] * bs + cworkB[i] % bs;
1247: else break;
1248: }
1249: imark = i;
1250: }
1251: for (i = 0; i < nzA; i++) idx_p[imark + i] = cstart * bs + cworkA[i];
1252: for (i = imark; i < nzB; i++) idx_p[nzA + i] = cmap[cworkB[i] / bs] * bs + cworkB[i] % bs;
1253: }
1254: } else {
1255: if (idx) *idx = NULL;
1256: if (v) *v = NULL;
1257: }
1258: }
1259: *nz = nztot;
1260: PetscCall((*mat->A->ops->restorerow)(mat->A, lrow, &nzA, pcA, pvA));
1261: PetscCall((*mat->B->ops->restorerow)(mat->B, lrow, &nzB, pcB, pvB));
1262: PetscFunctionReturn(PETSC_SUCCESS);
1263: }
1265: static PetscErrorCode MatRestoreRow_MPISBAIJ(Mat mat, PetscInt row, PetscInt *nz, PetscInt **idx, PetscScalar **v)
1266: {
1267: Mat_MPISBAIJ *baij = (Mat_MPISBAIJ *)mat->data;
1269: PetscFunctionBegin;
1270: PetscCheck(baij->getrowactive, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONGSTATE, "MatGetRow() must be called first");
1271: baij->getrowactive = PETSC_FALSE;
1272: PetscFunctionReturn(PETSC_SUCCESS);
1273: }
1275: static PetscErrorCode MatGetRowUpperTriangular_MPISBAIJ(Mat A)
1276: {
1277: Mat_MPISBAIJ *a = (Mat_MPISBAIJ *)A->data;
1278: Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ *)a->A->data;
1280: PetscFunctionBegin;
1281: aA->getrow_utriangular = PETSC_TRUE;
1282: PetscFunctionReturn(PETSC_SUCCESS);
1283: }
1284: static PetscErrorCode MatRestoreRowUpperTriangular_MPISBAIJ(Mat A)
1285: {
1286: Mat_MPISBAIJ *a = (Mat_MPISBAIJ *)A->data;
1287: Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ *)a->A->data;
1289: PetscFunctionBegin;
1290: aA->getrow_utriangular = PETSC_FALSE;
1291: PetscFunctionReturn(PETSC_SUCCESS);
1292: }
1294: static PetscErrorCode MatConjugate_MPISBAIJ(Mat mat)
1295: {
1296: PetscFunctionBegin;
1297: if (PetscDefined(USE_COMPLEX)) {
1298: Mat_MPISBAIJ *a = (Mat_MPISBAIJ *)mat->data;
1300: PetscCall(MatConjugate(a->A));
1301: PetscCall(MatConjugate(a->B));
1302: }
1303: PetscFunctionReturn(PETSC_SUCCESS);
1304: }
1306: static PetscErrorCode MatRealPart_MPISBAIJ(Mat A)
1307: {
1308: Mat_MPISBAIJ *a = (Mat_MPISBAIJ *)A->data;
1310: PetscFunctionBegin;
1311: PetscCall(MatRealPart(a->A));
1312: PetscCall(MatRealPart(a->B));
1313: PetscFunctionReturn(PETSC_SUCCESS);
1314: }
1316: static PetscErrorCode MatImaginaryPart_MPISBAIJ(Mat A)
1317: {
1318: Mat_MPISBAIJ *a = (Mat_MPISBAIJ *)A->data;
1320: PetscFunctionBegin;
1321: PetscCall(MatImaginaryPart(a->A));
1322: PetscCall(MatImaginaryPart(a->B));
1323: PetscFunctionReturn(PETSC_SUCCESS);
1324: }
1326: /* Check if isrow is a subset of iscol_local, called by MatCreateSubMatrix_MPISBAIJ()
1327: Input: isrow - distributed(parallel),
1328: iscol_local - locally owned (seq)
1329: */
1330: static PetscErrorCode ISEqual_private(IS isrow, IS iscol_local, PetscBool *flg)
1331: {
1332: PetscInt sz1, sz2, *a1, *a2, i, j, k, nmatch;
1333: const PetscInt *ptr1, *ptr2;
1335: PetscFunctionBegin;
1336: *flg = PETSC_FALSE;
1337: PetscCall(ISGetLocalSize(isrow, &sz1));
1338: PetscCall(ISGetLocalSize(iscol_local, &sz2));
1339: if (sz1 > sz2) PetscFunctionReturn(PETSC_SUCCESS);
1341: PetscCall(ISGetIndices(isrow, &ptr1));
1342: PetscCall(ISGetIndices(iscol_local, &ptr2));
1344: PetscCall(PetscMalloc1(sz1, &a1));
1345: PetscCall(PetscMalloc1(sz2, &a2));
1346: PetscCall(PetscArraycpy(a1, ptr1, sz1));
1347: PetscCall(PetscArraycpy(a2, ptr2, sz2));
1348: PetscCall(PetscSortInt(sz1, a1));
1349: PetscCall(PetscSortInt(sz2, a2));
1351: nmatch = 0;
1352: k = 0;
1353: for (i = 0; i < sz1; i++) {
1354: for (j = k; j < sz2; j++) {
1355: if (a1[i] == a2[j]) {
1356: k = j;
1357: nmatch++;
1358: break;
1359: }
1360: }
1361: }
1362: PetscCall(ISRestoreIndices(isrow, &ptr1));
1363: PetscCall(ISRestoreIndices(iscol_local, &ptr2));
1364: PetscCall(PetscFree(a1));
1365: PetscCall(PetscFree(a2));
1366: if (nmatch < sz1) {
1367: *flg = PETSC_FALSE;
1368: } else {
1369: *flg = PETSC_TRUE;
1370: }
1371: PetscFunctionReturn(PETSC_SUCCESS);
1372: }
1374: static PetscErrorCode MatCreateSubMatrix_MPISBAIJ(Mat mat, IS isrow, IS iscol, MatReuse call, Mat *newmat)
1375: {
1376: Mat C[2];
1377: IS iscol_local, isrow_local;
1378: PetscInt csize, csize_local, rsize;
1379: PetscBool isequal, issorted, isidentity = PETSC_FALSE;
1381: PetscFunctionBegin;
1382: PetscCall(ISGetLocalSize(iscol, &csize));
1383: PetscCall(ISGetLocalSize(isrow, &rsize));
1384: if (call == MAT_REUSE_MATRIX) {
1385: PetscCall(PetscObjectQuery((PetscObject)*newmat, "ISAllGather", (PetscObject *)&iscol_local));
1386: PetscCheck(iscol_local, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONGSTATE, "Submatrix passed in was not used before, cannot reuse");
1387: } else {
1388: PetscCall(ISAllGather(iscol, &iscol_local));
1389: PetscCall(ISSorted(iscol_local, &issorted));
1390: PetscCheck(issorted, PETSC_COMM_SELF, PETSC_ERR_ARG_INCOMP, "For symmetric format, iscol must be sorted");
1391: }
1392: PetscCall(ISEqual_private(isrow, iscol_local, &isequal));
1393: if (!isequal) {
1394: PetscCall(ISGetLocalSize(iscol_local, &csize_local));
1395: isidentity = (PetscBool)(mat->cmap->N == csize_local);
1396: if (!isidentity) {
1397: if (call == MAT_REUSE_MATRIX) {
1398: PetscCall(PetscObjectQuery((PetscObject)*newmat, "ISAllGather_other", (PetscObject *)&isrow_local));
1399: PetscCheck(isrow_local, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONGSTATE, "Submatrix passed in was not used before, cannot reuse");
1400: } else {
1401: PetscCall(ISAllGather(isrow, &isrow_local));
1402: PetscCall(ISSorted(isrow_local, &issorted));
1403: PetscCheck(issorted, PETSC_COMM_SELF, PETSC_ERR_ARG_INCOMP, "For symmetric format, isrow must be sorted");
1404: }
1405: }
1406: }
1407: /* now call MatCreateSubMatrix_MPIBAIJ() */
1408: PetscCall(MatCreateSubMatrix_MPIBAIJ_Private(mat, isrow, iscol_local, csize, isequal || isidentity ? call : MAT_INITIAL_MATRIX, isequal || isidentity ? newmat : C, (PetscBool)(isequal || isidentity)));
1409: if (!isequal && !isidentity) {
1410: if (call == MAT_INITIAL_MATRIX) {
1411: IS intersect;
1412: PetscInt ni;
1414: PetscCall(ISIntersect(isrow_local, iscol_local, &intersect));
1415: PetscCall(ISGetLocalSize(intersect, &ni));
1416: PetscCall(ISDestroy(&intersect));
1417: PetscCheck(ni == 0, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Cannot create such a submatrix: for symmetric format, when requesting an off-diagonal submatrix, isrow and iscol should have an empty intersection (number of common indices is %" PetscInt_FMT ")", ni);
1418: }
1419: PetscCall(MatCreateSubMatrix_MPIBAIJ_Private(mat, iscol, isrow_local, rsize, MAT_INITIAL_MATRIX, C + 1, PETSC_FALSE));
1420: PetscCall(MatTranspose(C[1], MAT_INPLACE_MATRIX, C + 1));
1421: PetscCall(MatAXPY(C[0], 1.0, C[1], DIFFERENT_NONZERO_PATTERN));
1422: if (call == MAT_REUSE_MATRIX) PetscCall(MatCopy(C[0], *newmat, SAME_NONZERO_PATTERN));
1423: else if (mat->rmap->bs == 1) PetscCall(MatConvert(C[0], MATAIJ, MAT_INITIAL_MATRIX, newmat));
1424: else PetscCall(MatCopy(C[0], *newmat, SAME_NONZERO_PATTERN));
1425: PetscCall(MatDestroy(C));
1426: PetscCall(MatDestroy(C + 1));
1427: }
1428: if (call == MAT_INITIAL_MATRIX) {
1429: if (!isequal && !isidentity) {
1430: PetscCall(PetscObjectCompose((PetscObject)*newmat, "ISAllGather_other", (PetscObject)isrow_local));
1431: PetscCall(ISDestroy(&isrow_local));
1432: }
1433: PetscCall(PetscObjectCompose((PetscObject)*newmat, "ISAllGather", (PetscObject)iscol_local));
1434: PetscCall(ISDestroy(&iscol_local));
1435: }
1436: PetscFunctionReturn(PETSC_SUCCESS);
1437: }
1439: static PetscErrorCode MatZeroEntries_MPISBAIJ(Mat A)
1440: {
1441: Mat_MPISBAIJ *l = (Mat_MPISBAIJ *)A->data;
1443: PetscFunctionBegin;
1444: PetscCall(MatZeroEntries(l->A));
1445: PetscCall(MatZeroEntries(l->B));
1446: PetscFunctionReturn(PETSC_SUCCESS);
1447: }
1449: static PetscErrorCode MatGetInfo_MPISBAIJ(Mat matin, MatInfoType flag, MatInfo *info)
1450: {
1451: Mat_MPISBAIJ *a = (Mat_MPISBAIJ *)matin->data;
1452: Mat A = a->A, B = a->B;
1453: PetscLogDouble isend[5], irecv[5];
1455: PetscFunctionBegin;
1456: info->block_size = (PetscReal)matin->rmap->bs;
1458: PetscCall(MatGetInfo(A, MAT_LOCAL, info));
1460: isend[0] = info->nz_used;
1461: isend[1] = info->nz_allocated;
1462: isend[2] = info->nz_unneeded;
1463: isend[3] = info->memory;
1464: isend[4] = info->mallocs;
1466: PetscCall(MatGetInfo(B, MAT_LOCAL, info));
1468: isend[0] += info->nz_used;
1469: isend[1] += info->nz_allocated;
1470: isend[2] += info->nz_unneeded;
1471: isend[3] += info->memory;
1472: isend[4] += info->mallocs;
1473: if (flag == MAT_LOCAL) {
1474: info->nz_used = isend[0];
1475: info->nz_allocated = isend[1];
1476: info->nz_unneeded = isend[2];
1477: info->memory = isend[3];
1478: info->mallocs = isend[4];
1479: } else if (flag == MAT_GLOBAL_MAX) {
1480: PetscCallMPI(MPIU_Allreduce(isend, irecv, 5, MPIU_PETSCLOGDOUBLE, MPI_MAX, PetscObjectComm((PetscObject)matin)));
1482: info->nz_used = irecv[0];
1483: info->nz_allocated = irecv[1];
1484: info->nz_unneeded = irecv[2];
1485: info->memory = irecv[3];
1486: info->mallocs = irecv[4];
1487: } else if (flag == MAT_GLOBAL_SUM) {
1488: PetscCallMPI(MPIU_Allreduce(isend, irecv, 5, MPIU_PETSCLOGDOUBLE, MPI_SUM, PetscObjectComm((PetscObject)matin)));
1490: info->nz_used = irecv[0];
1491: info->nz_allocated = irecv[1];
1492: info->nz_unneeded = irecv[2];
1493: info->memory = irecv[3];
1494: info->mallocs = irecv[4];
1495: } else SETERRQ(PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Unknown MatInfoType argument %d", (int)flag);
1496: info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */
1497: info->fill_ratio_needed = 0;
1498: info->factor_mallocs = 0;
1499: PetscFunctionReturn(PETSC_SUCCESS);
1500: }
1502: static PetscErrorCode MatSetOption_MPISBAIJ(Mat A, MatOption op, PetscBool flg)
1503: {
1504: Mat_MPISBAIJ *a = (Mat_MPISBAIJ *)A->data;
1505: Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ *)a->A->data;
1507: PetscFunctionBegin;
1508: switch (op) {
1509: case MAT_NEW_NONZERO_LOCATIONS:
1510: case MAT_NEW_NONZERO_ALLOCATION_ERR:
1511: case MAT_UNUSED_NONZERO_LOCATION_ERR:
1512: case MAT_KEEP_NONZERO_PATTERN:
1513: case MAT_NEW_NONZERO_LOCATION_ERR:
1514: MatCheckPreallocated(A, 1);
1515: PetscCall(MatSetOption(a->A, op, flg));
1516: PetscCall(MatSetOption(a->B, op, flg));
1517: break;
1518: case MAT_ROW_ORIENTED:
1519: MatCheckPreallocated(A, 1);
1520: a->roworiented = flg;
1522: PetscCall(MatSetOption(a->A, op, flg));
1523: PetscCall(MatSetOption(a->B, op, flg));
1524: break;
1525: case MAT_IGNORE_OFF_PROC_ENTRIES:
1526: a->donotstash = flg;
1527: break;
1528: case MAT_USE_HASH_TABLE:
1529: a->ht_flag = flg;
1530: break;
1531: case MAT_HERMITIAN:
1532: if (a->A && A->rmap->n == A->cmap->n) PetscCall(MatSetOption(a->A, op, flg));
1533: #if defined(PETSC_USE_COMPLEX)
1534: if (flg) { /* need different mat-vec ops */
1535: A->ops->mult = MatMult_MPISBAIJ_Hermitian;
1536: A->ops->multadd = MatMultAdd_MPISBAIJ_Hermitian;
1537: A->ops->multtranspose = NULL;
1538: A->ops->multtransposeadd = NULL;
1539: A->symmetric = PETSC_BOOL3_FALSE;
1540: }
1541: #endif
1542: break;
1543: case MAT_SPD:
1544: case MAT_SYMMETRIC:
1545: if (a->A && A->rmap->n == A->cmap->n) PetscCall(MatSetOption(a->A, op, flg));
1546: #if defined(PETSC_USE_COMPLEX)
1547: if (flg) { /* restore to use default mat-vec ops */
1548: A->ops->mult = MatMult_MPISBAIJ;
1549: A->ops->multadd = MatMultAdd_MPISBAIJ;
1550: A->ops->multtranspose = MatMult_MPISBAIJ;
1551: A->ops->multtransposeadd = MatMultAdd_MPISBAIJ;
1552: }
1553: #endif
1554: break;
1555: case MAT_STRUCTURALLY_SYMMETRIC:
1556: if (a->A && A->rmap->n == A->cmap->n) PetscCall(MatSetOption(a->A, op, flg));
1557: break;
1558: case MAT_IGNORE_LOWER_TRIANGULAR:
1559: case MAT_ERROR_LOWER_TRIANGULAR:
1560: aA->ignore_ltriangular = flg;
1561: break;
1562: case MAT_GETROW_UPPERTRIANGULAR:
1563: aA->getrow_utriangular = flg;
1564: break;
1565: default:
1566: break;
1567: }
1568: PetscFunctionReturn(PETSC_SUCCESS);
1569: }
1571: static PetscErrorCode MatTranspose_MPISBAIJ(Mat A, MatReuse reuse, Mat *B)
1572: {
1573: PetscFunctionBegin;
1574: if (reuse == MAT_REUSE_MATRIX) PetscCall(MatTransposeCheckNonzeroState_Private(A, *B));
1575: if (reuse == MAT_INITIAL_MATRIX) {
1576: PetscCall(MatDuplicate(A, MAT_COPY_VALUES, B));
1577: } else if (reuse == MAT_REUSE_MATRIX) {
1578: PetscCall(MatCopy(A, *B, SAME_NONZERO_PATTERN));
1579: }
1580: PetscFunctionReturn(PETSC_SUCCESS);
1581: }
1583: static PetscErrorCode MatDiagonalScale_MPISBAIJ(Mat mat, Vec ll, Vec rr)
1584: {
1585: Mat_MPISBAIJ *baij = (Mat_MPISBAIJ *)mat->data;
1586: Mat a = baij->A, b = baij->B;
1587: PetscInt nv, m, n;
1588: PetscBool flg;
1590: PetscFunctionBegin;
1591: if (ll != rr) {
1592: PetscCall(VecEqual(ll, rr, &flg));
1593: PetscCheck(flg, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "For symmetric format, left and right scaling vectors must be same");
1594: }
1595: if (!ll) PetscFunctionReturn(PETSC_SUCCESS);
1597: PetscCall(MatGetLocalSize(mat, &m, &n));
1598: PetscCheck(m == n, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "For symmetric format, local size %" PetscInt_FMT " %" PetscInt_FMT " must be same", m, n);
1600: PetscCall(VecGetLocalSize(rr, &nv));
1601: PetscCheck(nv == n, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Left and right vector non-conforming local size");
1603: PetscCall(VecScatterBegin(baij->Mvctx, rr, baij->lvec, INSERT_VALUES, SCATTER_FORWARD));
1605: /* left diagonalscale the off-diagonal part */
1606: PetscUseTypeMethod(b, diagonalscale, ll, NULL);
1608: /* scale the diagonal part */
1609: PetscUseTypeMethod(a, diagonalscale, ll, rr);
1611: /* right diagonalscale the off-diagonal part */
1612: PetscCall(VecScatterEnd(baij->Mvctx, rr, baij->lvec, INSERT_VALUES, SCATTER_FORWARD));
1613: PetscUseTypeMethod(b, diagonalscale, NULL, baij->lvec);
1614: PetscFunctionReturn(PETSC_SUCCESS);
1615: }
1617: static PetscErrorCode MatSetUnfactored_MPISBAIJ(Mat A)
1618: {
1619: Mat_MPISBAIJ *a = (Mat_MPISBAIJ *)A->data;
1621: PetscFunctionBegin;
1622: PetscCall(MatSetUnfactored(a->A));
1623: PetscFunctionReturn(PETSC_SUCCESS);
1624: }
1626: static PetscErrorCode MatDuplicate_MPISBAIJ(Mat, MatDuplicateOption, Mat *);
1628: static PetscErrorCode MatEqual_MPISBAIJ(Mat A, Mat B, PetscBool *flag)
1629: {
1630: Mat_MPISBAIJ *matB = (Mat_MPISBAIJ *)B->data, *matA = (Mat_MPISBAIJ *)A->data;
1631: Mat a, b, c, d;
1632: PetscBool flg;
1634: PetscFunctionBegin;
1635: a = matA->A;
1636: b = matA->B;
1637: c = matB->A;
1638: d = matB->B;
1640: PetscCall(MatEqual(a, c, &flg));
1641: if (flg) PetscCall(MatEqual(b, d, &flg));
1642: PetscCallMPI(MPIU_Allreduce(&flg, flag, 1, MPIU_BOOL, MPI_LAND, PetscObjectComm((PetscObject)A)));
1643: PetscFunctionReturn(PETSC_SUCCESS);
1644: }
1646: static PetscErrorCode MatCopy_MPISBAIJ(Mat A, Mat B, MatStructure str)
1647: {
1648: PetscBool isbaij;
1650: PetscFunctionBegin;
1651: PetscCall(PetscObjectTypeCompareAny((PetscObject)B, &isbaij, MATSEQSBAIJ, MATMPISBAIJ, ""));
1652: PetscCheck(isbaij, PetscObjectComm((PetscObject)B), PETSC_ERR_SUP, "Not for matrix type %s", ((PetscObject)B)->type_name);
1653: /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */
1654: if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) {
1655: PetscCall(MatGetRowUpperTriangular(A));
1656: PetscCall(MatCopy_Basic(A, B, str));
1657: PetscCall(MatRestoreRowUpperTriangular(A));
1658: } else {
1659: Mat_MPISBAIJ *a = (Mat_MPISBAIJ *)A->data;
1660: Mat_MPISBAIJ *b = (Mat_MPISBAIJ *)B->data;
1662: PetscCall(MatCopy(a->A, b->A, str));
1663: PetscCall(MatCopy(a->B, b->B, str));
1664: }
1665: PetscCall(PetscObjectStateIncrease((PetscObject)B));
1666: PetscFunctionReturn(PETSC_SUCCESS);
1667: }
1669: static PetscErrorCode MatAXPY_MPISBAIJ(Mat Y, PetscScalar a, Mat X, MatStructure str)
1670: {
1671: Mat_MPISBAIJ *xx = (Mat_MPISBAIJ *)X->data, *yy = (Mat_MPISBAIJ *)Y->data;
1672: PetscBLASInt bnz, one = 1;
1673: Mat_SeqSBAIJ *xa, *ya;
1674: Mat_SeqBAIJ *xb, *yb;
1676: PetscFunctionBegin;
1677: if (str == SAME_NONZERO_PATTERN) {
1678: PetscScalar alpha = a;
1679: xa = (Mat_SeqSBAIJ *)xx->A->data;
1680: ya = (Mat_SeqSBAIJ *)yy->A->data;
1681: PetscCall(PetscBLASIntCast(xa->nz, &bnz));
1682: PetscCallBLAS("BLASaxpy", BLASaxpy_(&bnz, &alpha, xa->a, &one, ya->a, &one));
1683: xb = (Mat_SeqBAIJ *)xx->B->data;
1684: yb = (Mat_SeqBAIJ *)yy->B->data;
1685: PetscCall(PetscBLASIntCast(xb->nz, &bnz));
1686: PetscCallBLAS("BLASaxpy", BLASaxpy_(&bnz, &alpha, xb->a, &one, yb->a, &one));
1687: PetscCall(PetscObjectStateIncrease((PetscObject)Y));
1688: } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */
1689: PetscCall(MatSetOption(X, MAT_GETROW_UPPERTRIANGULAR, PETSC_TRUE));
1690: PetscCall(MatAXPY_Basic(Y, a, X, str));
1691: PetscCall(MatSetOption(X, MAT_GETROW_UPPERTRIANGULAR, PETSC_FALSE));
1692: } else {
1693: Mat B;
1694: PetscInt *nnz_d, *nnz_o, bs = Y->rmap->bs;
1695: PetscCheck(bs == X->rmap->bs, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Matrices must have same block size");
1696: PetscCall(MatGetRowUpperTriangular(X));
1697: PetscCall(MatGetRowUpperTriangular(Y));
1698: PetscCall(PetscMalloc1(yy->A->rmap->N, &nnz_d));
1699: PetscCall(PetscMalloc1(yy->B->rmap->N, &nnz_o));
1700: PetscCall(MatCreate(PetscObjectComm((PetscObject)Y), &B));
1701: PetscCall(PetscObjectSetName((PetscObject)B, ((PetscObject)Y)->name));
1702: PetscCall(MatSetSizes(B, Y->rmap->n, Y->cmap->n, Y->rmap->N, Y->cmap->N));
1703: PetscCall(MatSetBlockSizesFromMats(B, Y, Y));
1704: PetscCall(MatSetType(B, MATMPISBAIJ));
1705: PetscCall(MatAXPYGetPreallocation_SeqSBAIJ(yy->A, xx->A, nnz_d));
1706: PetscCall(MatAXPYGetPreallocation_MPIBAIJ(yy->B, yy->garray, xx->B, xx->garray, nnz_o));
1707: PetscCall(MatMPISBAIJSetPreallocation(B, bs, 0, nnz_d, 0, nnz_o));
1708: PetscCall(MatAXPY_BasicWithPreallocation(B, Y, a, X, str));
1709: PetscCall(MatHeaderMerge(Y, &B));
1710: PetscCall(PetscFree(nnz_d));
1711: PetscCall(PetscFree(nnz_o));
1712: PetscCall(MatRestoreRowUpperTriangular(X));
1713: PetscCall(MatRestoreRowUpperTriangular(Y));
1714: }
1715: PetscFunctionReturn(PETSC_SUCCESS);
1716: }
1718: static PetscErrorCode MatCreateSubMatrices_MPISBAIJ(Mat A, PetscInt n, const IS irow[], const IS icol[], MatReuse scall, Mat *B[])
1719: {
1720: PetscInt i;
1721: PetscBool flg;
1723: PetscFunctionBegin;
1724: PetscCall(MatCreateSubMatrices_MPIBAIJ(A, n, irow, icol, scall, B)); /* B[] are sbaij matrices */
1725: for (i = 0; i < n; i++) {
1726: PetscCall(ISEqual(irow[i], icol[i], &flg));
1727: if (!flg) PetscCall(MatSeqSBAIJZeroOps_Private(*B[i]));
1728: }
1729: PetscFunctionReturn(PETSC_SUCCESS);
1730: }
1732: static PetscErrorCode MatShift_MPISBAIJ(Mat Y, PetscScalar a)
1733: {
1734: Mat_MPISBAIJ *maij = (Mat_MPISBAIJ *)Y->data;
1735: Mat_SeqSBAIJ *aij = (Mat_SeqSBAIJ *)maij->A->data;
1737: PetscFunctionBegin;
1738: if (!Y->preallocated) {
1739: PetscCall(MatMPISBAIJSetPreallocation(Y, Y->rmap->bs, 1, NULL, 0, NULL));
1740: } else if (!aij->nz) {
1741: PetscInt nonew = aij->nonew;
1742: PetscCall(MatSeqSBAIJSetPreallocation(maij->A, Y->rmap->bs, 1, NULL));
1743: aij->nonew = nonew;
1744: }
1745: PetscCall(MatShift_Basic(Y, a));
1746: PetscFunctionReturn(PETSC_SUCCESS);
1747: }
1749: static PetscErrorCode MatMissingDiagonal_MPISBAIJ(Mat A, PetscBool *missing, PetscInt *d)
1750: {
1751: Mat_MPISBAIJ *a = (Mat_MPISBAIJ *)A->data;
1753: PetscFunctionBegin;
1754: PetscCheck(A->rmap->n == A->cmap->n, PETSC_COMM_SELF, PETSC_ERR_SUP, "Only works for square matrices");
1755: PetscCall(MatMissingDiagonal(a->A, missing, d));
1756: if (d) {
1757: PetscInt rstart;
1758: PetscCall(MatGetOwnershipRange(A, &rstart, NULL));
1759: *d += rstart / A->rmap->bs;
1760: }
1761: PetscFunctionReturn(PETSC_SUCCESS);
1762: }
1764: static PetscErrorCode MatGetDiagonalBlock_MPISBAIJ(Mat A, Mat *a)
1765: {
1766: PetscFunctionBegin;
1767: *a = ((Mat_MPISBAIJ *)A->data)->A;
1768: PetscFunctionReturn(PETSC_SUCCESS);
1769: }
1771: static PetscErrorCode MatEliminateZeros_MPISBAIJ(Mat A, PetscBool keep)
1772: {
1773: Mat_MPISBAIJ *a = (Mat_MPISBAIJ *)A->data;
1775: PetscFunctionBegin;
1776: PetscCall(MatEliminateZeros_SeqSBAIJ(a->A, keep)); // possibly keep zero diagonal coefficients
1777: PetscCall(MatEliminateZeros_SeqBAIJ(a->B, PETSC_FALSE)); // never keep zero diagonal coefficients
1778: PetscFunctionReturn(PETSC_SUCCESS);
1779: }
1781: static PetscErrorCode MatLoad_MPISBAIJ(Mat, PetscViewer);
1782: static PetscErrorCode MatGetRowMaxAbs_MPISBAIJ(Mat, Vec, PetscInt[]);
1783: static PetscErrorCode MatSOR_MPISBAIJ(Mat, Vec, PetscReal, MatSORType, PetscReal, PetscInt, PetscInt, Vec);
1785: static struct _MatOps MatOps_Values = {MatSetValues_MPISBAIJ,
1786: MatGetRow_MPISBAIJ,
1787: MatRestoreRow_MPISBAIJ,
1788: MatMult_MPISBAIJ,
1789: /* 4*/ MatMultAdd_MPISBAIJ,
1790: MatMult_MPISBAIJ, /* transpose versions are same as non-transpose */
1791: MatMultAdd_MPISBAIJ,
1792: NULL,
1793: NULL,
1794: NULL,
1795: /* 10*/ NULL,
1796: NULL,
1797: NULL,
1798: MatSOR_MPISBAIJ,
1799: MatTranspose_MPISBAIJ,
1800: /* 15*/ MatGetInfo_MPISBAIJ,
1801: MatEqual_MPISBAIJ,
1802: MatGetDiagonal_MPISBAIJ,
1803: MatDiagonalScale_MPISBAIJ,
1804: MatNorm_MPISBAIJ,
1805: /* 20*/ MatAssemblyBegin_MPISBAIJ,
1806: MatAssemblyEnd_MPISBAIJ,
1807: MatSetOption_MPISBAIJ,
1808: MatZeroEntries_MPISBAIJ,
1809: /* 24*/ NULL,
1810: NULL,
1811: NULL,
1812: NULL,
1813: NULL,
1814: /* 29*/ MatSetUp_MPI_Hash,
1815: NULL,
1816: NULL,
1817: MatGetDiagonalBlock_MPISBAIJ,
1818: NULL,
1819: /* 34*/ MatDuplicate_MPISBAIJ,
1820: NULL,
1821: NULL,
1822: NULL,
1823: NULL,
1824: /* 39*/ MatAXPY_MPISBAIJ,
1825: MatCreateSubMatrices_MPISBAIJ,
1826: MatIncreaseOverlap_MPISBAIJ,
1827: MatGetValues_MPISBAIJ,
1828: MatCopy_MPISBAIJ,
1829: /* 44*/ NULL,
1830: MatScale_MPISBAIJ,
1831: MatShift_MPISBAIJ,
1832: NULL,
1833: NULL,
1834: /* 49*/ NULL,
1835: NULL,
1836: NULL,
1837: NULL,
1838: NULL,
1839: /* 54*/ NULL,
1840: NULL,
1841: MatSetUnfactored_MPISBAIJ,
1842: NULL,
1843: MatSetValuesBlocked_MPISBAIJ,
1844: /* 59*/ MatCreateSubMatrix_MPISBAIJ,
1845: NULL,
1846: NULL,
1847: NULL,
1848: NULL,
1849: /* 64*/ NULL,
1850: NULL,
1851: NULL,
1852: NULL,
1853: NULL,
1854: /* 69*/ MatGetRowMaxAbs_MPISBAIJ,
1855: NULL,
1856: MatConvert_MPISBAIJ_Basic,
1857: NULL,
1858: NULL,
1859: /* 74*/ NULL,
1860: NULL,
1861: NULL,
1862: NULL,
1863: NULL,
1864: /* 79*/ NULL,
1865: NULL,
1866: NULL,
1867: NULL,
1868: MatLoad_MPISBAIJ,
1869: /* 84*/ NULL,
1870: NULL,
1871: NULL,
1872: NULL,
1873: NULL,
1874: /* 89*/ NULL,
1875: NULL,
1876: NULL,
1877: NULL,
1878: NULL,
1879: /* 94*/ NULL,
1880: NULL,
1881: NULL,
1882: NULL,
1883: NULL,
1884: /* 99*/ NULL,
1885: NULL,
1886: NULL,
1887: MatConjugate_MPISBAIJ,
1888: NULL,
1889: /*104*/ NULL,
1890: MatRealPart_MPISBAIJ,
1891: MatImaginaryPart_MPISBAIJ,
1892: MatGetRowUpperTriangular_MPISBAIJ,
1893: MatRestoreRowUpperTriangular_MPISBAIJ,
1894: /*109*/ NULL,
1895: NULL,
1896: NULL,
1897: NULL,
1898: MatMissingDiagonal_MPISBAIJ,
1899: /*114*/ NULL,
1900: NULL,
1901: NULL,
1902: NULL,
1903: NULL,
1904: /*119*/ NULL,
1905: NULL,
1906: NULL,
1907: NULL,
1908: NULL,
1909: /*124*/ NULL,
1910: NULL,
1911: NULL,
1912: NULL,
1913: NULL,
1914: /*129*/ NULL,
1915: NULL,
1916: NULL,
1917: NULL,
1918: NULL,
1919: /*134*/ NULL,
1920: NULL,
1921: NULL,
1922: NULL,
1923: NULL,
1924: /*139*/ MatSetBlockSizes_Default,
1925: NULL,
1926: NULL,
1927: NULL,
1928: NULL,
1929: /*144*/ MatCreateMPIMatConcatenateSeqMat_MPISBAIJ,
1930: NULL,
1931: NULL,
1932: NULL,
1933: NULL,
1934: NULL,
1935: /*150*/ NULL,
1936: MatEliminateZeros_MPISBAIJ,
1937: NULL,
1938: NULL,
1939: NULL,
1940: /*155*/ NULL,
1941: MatCopyHashToXAIJ_MPI_Hash};
1943: static PetscErrorCode MatMPISBAIJSetPreallocation_MPISBAIJ(Mat B, PetscInt bs, PetscInt d_nz, const PetscInt *d_nnz, PetscInt o_nz, const PetscInt *o_nnz)
1944: {
1945: Mat_MPISBAIJ *b = (Mat_MPISBAIJ *)B->data;
1946: PetscInt i, mbs, Mbs;
1947: PetscMPIInt size;
1949: PetscFunctionBegin;
1950: if (B->hash_active) {
1951: B->ops[0] = b->cops;
1952: B->hash_active = PETSC_FALSE;
1953: }
1954: if (!B->preallocated) PetscCall(MatStashCreate_Private(PetscObjectComm((PetscObject)B), bs, &B->bstash));
1955: PetscCall(MatSetBlockSize(B, bs));
1956: PetscCall(PetscLayoutSetUp(B->rmap));
1957: PetscCall(PetscLayoutSetUp(B->cmap));
1958: PetscCall(PetscLayoutGetBlockSize(B->rmap, &bs));
1959: PetscCheck(B->rmap->N <= B->cmap->N, PetscObjectComm((PetscObject)B), PETSC_ERR_SUP, "MPISBAIJ matrix cannot have more rows %" PetscInt_FMT " than columns %" PetscInt_FMT, B->rmap->N, B->cmap->N);
1960: PetscCheck(B->rmap->n <= B->cmap->n, PETSC_COMM_SELF, PETSC_ERR_SUP, "MPISBAIJ matrix cannot have more local rows %" PetscInt_FMT " than columns %" PetscInt_FMT, B->rmap->n, B->cmap->n);
1962: mbs = B->rmap->n / bs;
1963: Mbs = B->rmap->N / bs;
1964: PetscCheck(mbs * bs == B->rmap->n, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "No of local rows %" PetscInt_FMT " must be divisible by blocksize %" PetscInt_FMT, B->rmap->N, bs);
1966: B->rmap->bs = bs;
1967: b->bs2 = bs * bs;
1968: b->mbs = mbs;
1969: b->Mbs = Mbs;
1970: b->nbs = B->cmap->n / bs;
1971: b->Nbs = B->cmap->N / bs;
1973: for (i = 0; i <= b->size; i++) b->rangebs[i] = B->rmap->range[i] / bs;
1974: b->rstartbs = B->rmap->rstart / bs;
1975: b->rendbs = B->rmap->rend / bs;
1977: b->cstartbs = B->cmap->rstart / bs;
1978: b->cendbs = B->cmap->rend / bs;
1980: #if defined(PETSC_USE_CTABLE)
1981: PetscCall(PetscHMapIDestroy(&b->colmap));
1982: #else
1983: PetscCall(PetscFree(b->colmap));
1984: #endif
1985: PetscCall(PetscFree(b->garray));
1986: PetscCall(VecDestroy(&b->lvec));
1987: PetscCall(VecScatterDestroy(&b->Mvctx));
1988: PetscCall(VecDestroy(&b->slvec0));
1989: PetscCall(VecDestroy(&b->slvec0b));
1990: PetscCall(VecDestroy(&b->slvec1));
1991: PetscCall(VecDestroy(&b->slvec1a));
1992: PetscCall(VecDestroy(&b->slvec1b));
1993: PetscCall(VecScatterDestroy(&b->sMvctx));
1995: PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)B), &size));
1997: MatSeqXAIJGetOptions_Private(b->B);
1998: PetscCall(MatDestroy(&b->B));
1999: PetscCall(MatCreate(PETSC_COMM_SELF, &b->B));
2000: PetscCall(MatSetSizes(b->B, B->rmap->n, size > 1 ? B->cmap->N : 0, B->rmap->n, size > 1 ? B->cmap->N : 0));
2001: PetscCall(MatSetType(b->B, MATSEQBAIJ));
2002: MatSeqXAIJRestoreOptions_Private(b->B);
2004: MatSeqXAIJGetOptions_Private(b->A);
2005: PetscCall(MatDestroy(&b->A));
2006: PetscCall(MatCreate(PETSC_COMM_SELF, &b->A));
2007: PetscCall(MatSetSizes(b->A, B->rmap->n, B->cmap->n, B->rmap->n, B->cmap->n));
2008: PetscCall(MatSetType(b->A, MATSEQSBAIJ));
2009: MatSeqXAIJRestoreOptions_Private(b->A);
2011: PetscCall(MatSeqSBAIJSetPreallocation(b->A, bs, d_nz, d_nnz));
2012: PetscCall(MatSeqBAIJSetPreallocation(b->B, bs, o_nz, o_nnz));
2014: B->preallocated = PETSC_TRUE;
2015: B->was_assembled = PETSC_FALSE;
2016: B->assembled = PETSC_FALSE;
2017: PetscFunctionReturn(PETSC_SUCCESS);
2018: }
2020: static PetscErrorCode MatMPISBAIJSetPreallocationCSR_MPISBAIJ(Mat B, PetscInt bs, const PetscInt ii[], const PetscInt jj[], const PetscScalar V[])
2021: {
2022: PetscInt m, rstart, cend;
2023: PetscInt i, j, d, nz, bd, nz_max = 0, *d_nnz = NULL, *o_nnz = NULL;
2024: const PetscInt *JJ = NULL;
2025: PetscScalar *values = NULL;
2026: PetscBool roworiented = ((Mat_MPISBAIJ *)B->data)->roworiented;
2027: PetscBool nooffprocentries;
2029: PetscFunctionBegin;
2030: PetscCheck(bs >= 1, PetscObjectComm((PetscObject)B), PETSC_ERR_ARG_OUTOFRANGE, "Invalid block size specified, must be positive but it is %" PetscInt_FMT, bs);
2031: PetscCall(PetscLayoutSetBlockSize(B->rmap, bs));
2032: PetscCall(PetscLayoutSetBlockSize(B->cmap, bs));
2033: PetscCall(PetscLayoutSetUp(B->rmap));
2034: PetscCall(PetscLayoutSetUp(B->cmap));
2035: PetscCall(PetscLayoutGetBlockSize(B->rmap, &bs));
2036: m = B->rmap->n / bs;
2037: rstart = B->rmap->rstart / bs;
2038: cend = B->cmap->rend / bs;
2040: PetscCheck(!ii[0], PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "ii[0] must be 0 but it is %" PetscInt_FMT, ii[0]);
2041: PetscCall(PetscMalloc2(m, &d_nnz, m, &o_nnz));
2042: for (i = 0; i < m; i++) {
2043: nz = ii[i + 1] - ii[i];
2044: PetscCheck(nz >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Local row %" PetscInt_FMT " has a negative number of columns %" PetscInt_FMT, i, nz);
2045: /* count the ones on the diagonal and above, split into diagonal and off-diagonal portions. */
2046: JJ = jj + ii[i];
2047: bd = 0;
2048: for (j = 0; j < nz; j++) {
2049: if (*JJ >= i + rstart) break;
2050: JJ++;
2051: bd++;
2052: }
2053: d = 0;
2054: for (; j < nz; j++) {
2055: if (*JJ++ >= cend) break;
2056: d++;
2057: }
2058: d_nnz[i] = d;
2059: o_nnz[i] = nz - d - bd;
2060: nz = nz - bd;
2061: nz_max = PetscMax(nz_max, nz);
2062: }
2063: PetscCall(MatMPISBAIJSetPreallocation(B, bs, 0, d_nnz, 0, o_nnz));
2064: PetscCall(MatSetOption(B, MAT_IGNORE_LOWER_TRIANGULAR, PETSC_TRUE));
2065: PetscCall(PetscFree2(d_nnz, o_nnz));
2067: values = (PetscScalar *)V;
2068: if (!values) PetscCall(PetscCalloc1(bs * bs * nz_max, &values));
2069: for (i = 0; i < m; i++) {
2070: PetscInt row = i + rstart;
2071: PetscInt ncols = ii[i + 1] - ii[i];
2072: const PetscInt *icols = jj + ii[i];
2073: if (bs == 1 || !roworiented) { /* block ordering matches the non-nested layout of MatSetValues so we can insert entire rows */
2074: const PetscScalar *svals = values + (V ? (bs * bs * ii[i]) : 0);
2075: PetscCall(MatSetValuesBlocked_MPISBAIJ(B, 1, &row, ncols, icols, svals, INSERT_VALUES));
2076: } else { /* block ordering does not match so we can only insert one block at a time. */
2077: PetscInt j;
2078: for (j = 0; j < ncols; j++) {
2079: const PetscScalar *svals = values + (V ? (bs * bs * (ii[i] + j)) : 0);
2080: PetscCall(MatSetValuesBlocked_MPISBAIJ(B, 1, &row, 1, &icols[j], svals, INSERT_VALUES));
2081: }
2082: }
2083: }
2085: if (!V) PetscCall(PetscFree(values));
2086: nooffprocentries = B->nooffprocentries;
2087: B->nooffprocentries = PETSC_TRUE;
2088: PetscCall(MatAssemblyBegin(B, MAT_FINAL_ASSEMBLY));
2089: PetscCall(MatAssemblyEnd(B, MAT_FINAL_ASSEMBLY));
2090: B->nooffprocentries = nooffprocentries;
2092: PetscCall(MatSetOption(B, MAT_NEW_NONZERO_LOCATION_ERR, PETSC_TRUE));
2093: PetscFunctionReturn(PETSC_SUCCESS);
2094: }
2096: /*MC
2097: MATMPISBAIJ - MATMPISBAIJ = "mpisbaij" - A matrix type to be used for distributed symmetric sparse block matrices,
2098: based on block compressed sparse row format. Only the upper triangular portion of the "diagonal" portion of
2099: the matrix is stored.
2101: For complex numbers by default this matrix is symmetric, NOT Hermitian symmetric. To make it Hermitian symmetric you
2102: can call `MatSetOption`(`Mat`, `MAT_HERMITIAN`);
2104: Options Database Key:
2105: . -mat_type mpisbaij - sets the matrix type to "mpisbaij" during a call to `MatSetFromOptions()`
2107: Level: beginner
2109: Note:
2110: The number of rows in the matrix must be less than or equal to the number of columns. Similarly the number of rows in the
2111: diagonal portion of the matrix of each process has to less than or equal the number of columns.
2113: .seealso: [](ch_matrices), `Mat`, `MATSBAIJ`, `MATBAIJ`, `MatCreateBAIJ()`, `MATSEQSBAIJ`, `MatType`
2114: M*/
2116: PETSC_EXTERN PetscErrorCode MatCreate_MPISBAIJ(Mat B)
2117: {
2118: Mat_MPISBAIJ *b;
2119: PetscBool flg = PETSC_FALSE;
2121: PetscFunctionBegin;
2122: PetscCall(PetscNew(&b));
2123: B->data = (void *)b;
2124: B->ops[0] = MatOps_Values;
2126: B->ops->destroy = MatDestroy_MPISBAIJ;
2127: B->ops->view = MatView_MPISBAIJ;
2128: B->assembled = PETSC_FALSE;
2129: B->insertmode = NOT_SET_VALUES;
2131: PetscCallMPI(MPI_Comm_rank(PetscObjectComm((PetscObject)B), &b->rank));
2132: PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)B), &b->size));
2134: /* build local table of row and column ownerships */
2135: PetscCall(PetscMalloc1(b->size + 2, &b->rangebs));
2137: /* build cache for off array entries formed */
2138: PetscCall(MatStashCreate_Private(PetscObjectComm((PetscObject)B), 1, &B->stash));
2140: b->donotstash = PETSC_FALSE;
2141: b->colmap = NULL;
2142: b->garray = NULL;
2143: b->roworiented = PETSC_TRUE;
2145: /* stuff used in block assembly */
2146: b->barray = NULL;
2148: /* stuff used for matrix vector multiply */
2149: b->lvec = NULL;
2150: b->Mvctx = NULL;
2151: b->slvec0 = NULL;
2152: b->slvec0b = NULL;
2153: b->slvec1 = NULL;
2154: b->slvec1a = NULL;
2155: b->slvec1b = NULL;
2156: b->sMvctx = NULL;
2158: /* stuff for MatGetRow() */
2159: b->rowindices = NULL;
2160: b->rowvalues = NULL;
2161: b->getrowactive = PETSC_FALSE;
2163: /* hash table stuff */
2164: b->ht = NULL;
2165: b->hd = NULL;
2166: b->ht_size = 0;
2167: b->ht_flag = PETSC_FALSE;
2168: b->ht_fact = 0;
2169: b->ht_total_ct = 0;
2170: b->ht_insert_ct = 0;
2172: /* stuff for MatCreateSubMatrices_MPIBAIJ_local() */
2173: b->ijonly = PETSC_FALSE;
2175: b->in_loc = NULL;
2176: b->v_loc = NULL;
2177: b->n_loc = 0;
2179: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatStoreValues_C", MatStoreValues_MPISBAIJ));
2180: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatRetrieveValues_C", MatRetrieveValues_MPISBAIJ));
2181: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatMPISBAIJSetPreallocation_C", MatMPISBAIJSetPreallocation_MPISBAIJ));
2182: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatMPISBAIJSetPreallocationCSR_C", MatMPISBAIJSetPreallocationCSR_MPISBAIJ));
2183: #if defined(PETSC_HAVE_ELEMENTAL)
2184: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatConvert_mpisbaij_elemental_C", MatConvert_MPISBAIJ_Elemental));
2185: #endif
2186: #if defined(PETSC_HAVE_SCALAPACK)
2187: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatConvert_mpisbaij_scalapack_C", MatConvert_SBAIJ_ScaLAPACK));
2188: #endif
2189: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatConvert_mpisbaij_mpiaij_C", MatConvert_MPISBAIJ_Basic));
2190: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatConvert_mpisbaij_mpibaij_C", MatConvert_MPISBAIJ_Basic));
2192: B->symmetric = PETSC_BOOL3_TRUE;
2193: B->structurally_symmetric = PETSC_BOOL3_TRUE;
2194: B->symmetry_eternal = PETSC_TRUE;
2195: B->structural_symmetry_eternal = PETSC_TRUE;
2196: #if defined(PETSC_USE_COMPLEX)
2197: B->hermitian = PETSC_BOOL3_FALSE;
2198: #else
2199: B->hermitian = PETSC_BOOL3_TRUE;
2200: #endif
2202: PetscCall(PetscObjectChangeTypeName((PetscObject)B, MATMPISBAIJ));
2203: PetscOptionsBegin(PetscObjectComm((PetscObject)B), NULL, "Options for loading MPISBAIJ matrix 1", "Mat");
2204: PetscCall(PetscOptionsBool("-mat_use_hash_table", "Use hash table to save memory in constructing matrix", "MatSetOption", flg, &flg, NULL));
2205: if (flg) {
2206: PetscReal fact = 1.39;
2207: PetscCall(MatSetOption(B, MAT_USE_HASH_TABLE, PETSC_TRUE));
2208: PetscCall(PetscOptionsReal("-mat_use_hash_table", "Use hash table factor", "MatMPIBAIJSetHashTableFactor", fact, &fact, NULL));
2209: if (fact <= 1.0) fact = 1.39;
2210: PetscCall(MatMPIBAIJSetHashTableFactor(B, fact));
2211: PetscCall(PetscInfo(B, "Hash table Factor used %5.2g\n", (double)fact));
2212: }
2213: PetscOptionsEnd();
2214: PetscFunctionReturn(PETSC_SUCCESS);
2215: }
2217: // PetscClangLinter pragma disable: -fdoc-section-header-unknown
2218: /*MC
2219: MATSBAIJ - MATSBAIJ = "sbaij" - A matrix type to be used for symmetric block sparse matrices.
2221: This matrix type is identical to `MATSEQSBAIJ` when constructed with a single process communicator,
2222: and `MATMPISBAIJ` otherwise.
2224: Options Database Key:
2225: . -mat_type sbaij - sets the matrix type to `MATSBAIJ` during a call to `MatSetFromOptions()`
2227: Level: beginner
2229: .seealso: [](ch_matrices), `Mat`, `MATSEQSBAIJ`, `MATMPISBAIJ`, `MatCreateSBAIJ()`, `MATSEQSBAIJ`, `MATMPISBAIJ`
2230: M*/
2232: /*@
2233: MatMPISBAIJSetPreallocation - For good matrix assembly performance
2234: the user should preallocate the matrix storage by setting the parameters
2235: d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately,
2236: performance can be increased by more than a factor of 50.
2238: Collective
2240: Input Parameters:
2241: + B - the matrix
2242: . bs - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row
2243: blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs()
2244: . d_nz - number of block nonzeros per block row in diagonal portion of local
2245: submatrix (same for all local rows)
2246: . d_nnz - array containing the number of block nonzeros in the various block rows
2247: in the upper triangular and diagonal part of the in diagonal portion of the local
2248: (possibly different for each block row) or `NULL`. If you plan to factor the matrix you must leave room
2249: for the diagonal entry and set a value even if it is zero.
2250: . o_nz - number of block nonzeros per block row in the off-diagonal portion of local
2251: submatrix (same for all local rows).
2252: - o_nnz - array containing the number of nonzeros in the various block rows of the
2253: off-diagonal portion of the local submatrix that is right of the diagonal
2254: (possibly different for each block row) or `NULL`.
2256: Options Database Keys:
2257: + -mat_no_unroll - uses code that does not unroll the loops in the
2258: block calculations (much slower)
2259: - -mat_block_size - size of the blocks to use
2261: Level: intermediate
2263: Notes:
2265: If `PETSC_DECIDE` or `PETSC_DETERMINE` is used for a particular argument on one processor
2266: than it must be used on all processors that share the object for that argument.
2268: If the *_nnz parameter is given then the *_nz parameter is ignored
2270: Storage Information:
2271: For a square global matrix we define each processor's diagonal portion
2272: to be its local rows and the corresponding columns (a square submatrix);
2273: each processor's off-diagonal portion encompasses the remainder of the
2274: local matrix (a rectangular submatrix).
2276: The user can specify preallocated storage for the diagonal part of
2277: the local submatrix with either `d_nz` or `d_nnz` (not both). Set
2278: `d_nz` = `PETSC_DEFAULT` and `d_nnz` = `NULL` for PETSc to control dynamic
2279: memory allocation. Likewise, specify preallocated storage for the
2280: off-diagonal part of the local submatrix with `o_nz` or `o_nnz` (not both).
2282: You can call `MatGetInfo()` to get information on how effective the preallocation was;
2283: for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
2284: You can also run with the option `-info` and look for messages with the string
2285: malloc in them to see if additional memory allocation was needed.
2287: Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In
2288: the figure below we depict these three local rows and all columns (0-11).
2290: .vb
2291: 0 1 2 3 4 5 6 7 8 9 10 11
2292: --------------------------
2293: row 3 |. . . d d d o o o o o o
2294: row 4 |. . . d d d o o o o o o
2295: row 5 |. . . d d d o o o o o o
2296: --------------------------
2297: .ve
2299: Thus, any entries in the d locations are stored in the d (diagonal)
2300: submatrix, and any entries in the o locations are stored in the
2301: o (off-diagonal) submatrix. Note that the d matrix is stored in
2302: `MATSEQSBAIJ` format and the o submatrix in `MATSEQBAIJ` format.
2304: Now `d_nz` should indicate the number of block nonzeros per row in the upper triangular
2305: plus the diagonal part of the d matrix,
2306: and `o_nz` should indicate the number of block nonzeros per row in the o matrix
2308: In general, for PDE problems in which most nonzeros are near the diagonal,
2309: one expects `d_nz` >> `o_nz`.
2311: .seealso: [](ch_matrices), `Mat`, `MATMPISBAIJ`, `MATSBAIJ`, `MatCreate()`, `MatCreateSeqSBAIJ()`, `MatSetValues()`, `MatCreateBAIJ()`, `PetscSplitOwnership()`
2312: @*/
2313: PetscErrorCode MatMPISBAIJSetPreallocation(Mat B, PetscInt bs, PetscInt d_nz, const PetscInt d_nnz[], PetscInt o_nz, const PetscInt o_nnz[])
2314: {
2315: PetscFunctionBegin;
2319: PetscTryMethod(B, "MatMPISBAIJSetPreallocation_C", (Mat, PetscInt, PetscInt, const PetscInt[], PetscInt, const PetscInt[]), (B, bs, d_nz, d_nnz, o_nz, o_nnz));
2320: PetscFunctionReturn(PETSC_SUCCESS);
2321: }
2323: // PetscClangLinter pragma disable: -fdoc-section-header-unknown
2324: /*@
2325: MatCreateSBAIJ - Creates a sparse parallel matrix in symmetric block AIJ format, `MATSBAIJ`,
2326: (block compressed row). For good matrix assembly performance
2327: the user should preallocate the matrix storage by setting the parameters
2328: `d_nz` (or `d_nnz`) and `o_nz` (or `o_nnz`).
2330: Collective
2332: Input Parameters:
2333: + comm - MPI communicator
2334: . bs - size of block, the blocks are ALWAYS square. One can use `MatSetBlockSizes()` to set a different row and column blocksize but the row
2335: blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with `MatCreateVecs()`
2336: . m - number of local rows (or `PETSC_DECIDE` to have calculated if `M` is given)
2337: This value should be the same as the local size used in creating the
2338: y vector for the matrix-vector product y = Ax.
2339: . n - number of local columns (or `PETSC_DECIDE` to have calculated if `N` is given)
2340: This value should be the same as the local size used in creating the
2341: x vector for the matrix-vector product y = Ax.
2342: . M - number of global rows (or `PETSC_DETERMINE` to have calculated if `m` is given)
2343: . N - number of global columns (or `PETSC_DETERMINE` to have calculated if `n` is given)
2344: . d_nz - number of block nonzeros per block row in diagonal portion of local
2345: submatrix (same for all local rows)
2346: . d_nnz - array containing the number of block nonzeros in the various block rows
2347: in the upper triangular portion of the in diagonal portion of the local
2348: (possibly different for each block block row) or `NULL`.
2349: If you plan to factor the matrix you must leave room for the diagonal entry and
2350: set its value even if it is zero.
2351: . o_nz - number of block nonzeros per block row in the off-diagonal portion of local
2352: submatrix (same for all local rows).
2353: - o_nnz - array containing the number of nonzeros in the various block rows of the
2354: off-diagonal portion of the local submatrix (possibly different for
2355: each block row) or `NULL`.
2357: Output Parameter:
2358: . A - the matrix
2360: Options Database Keys:
2361: + -mat_no_unroll - uses code that does not unroll the loops in the
2362: block calculations (much slower)
2363: . -mat_block_size - size of the blocks to use
2364: - -mat_mpi - use the parallel matrix data structures even on one processor
2365: (defaults to using SeqBAIJ format on one processor)
2367: Level: intermediate
2369: Notes:
2370: It is recommended that one use `MatCreateFromOptions()` or the `MatCreate()`, `MatSetType()` and/or `MatSetFromOptions()`,
2371: MatXXXXSetPreallocation() paradigm instead of this routine directly.
2372: [MatXXXXSetPreallocation() is, for example, `MatSeqAIJSetPreallocation()`]
2374: The number of rows and columns must be divisible by blocksize.
2375: This matrix type does not support complex Hermitian operation.
2377: The user MUST specify either the local or global matrix dimensions
2378: (possibly both).
2380: If `PETSC_DECIDE` or `PETSC_DETERMINE` is used for a particular argument on one processor
2381: than it must be used on all processors that share the object for that argument.
2383: If `m` and `n` are not `PETSC_DECIDE`, then the values determines the `PetscLayout` of the matrix and the ranges returned by
2384: `MatGetOwnershipRange()`, `MatGetOwnershipRanges()`, `MatGetOwnershipRangeColumn()`, and `MatGetOwnershipRangesColumn()`.
2386: If the *_nnz parameter is given then the *_nz parameter is ignored
2388: Storage Information:
2389: For a square global matrix we define each processor's diagonal portion
2390: to be its local rows and the corresponding columns (a square submatrix);
2391: each processor's off-diagonal portion encompasses the remainder of the
2392: local matrix (a rectangular submatrix).
2394: The user can specify preallocated storage for the diagonal part of
2395: the local submatrix with either `d_nz` or `d_nnz` (not both). Set
2396: `d_nz` = `PETSC_DEFAULT` and `d_nnz` = `NULL` for PETSc to control dynamic
2397: memory allocation. Likewise, specify preallocated storage for the
2398: off-diagonal part of the local submatrix with `o_nz` or `o_nnz` (not both).
2400: Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In
2401: the figure below we depict these three local rows and all columns (0-11).
2403: .vb
2404: 0 1 2 3 4 5 6 7 8 9 10 11
2405: --------------------------
2406: row 3 |. . . d d d o o o o o o
2407: row 4 |. . . d d d o o o o o o
2408: row 5 |. . . d d d o o o o o o
2409: --------------------------
2410: .ve
2412: Thus, any entries in the d locations are stored in the d (diagonal)
2413: submatrix, and any entries in the o locations are stored in the
2414: o (off-diagonal) submatrix. Note that the d matrix is stored in
2415: `MATSEQSBAIJ` format and the o submatrix in `MATSEQBAIJ` format.
2417: Now `d_nz` should indicate the number of block nonzeros per row in the upper triangular
2418: plus the diagonal part of the d matrix,
2419: and `o_nz` should indicate the number of block nonzeros per row in the o matrix.
2420: In general, for PDE problems in which most nonzeros are near the diagonal,
2421: one expects `d_nz` >> `o_nz`.
2423: .seealso: [](ch_matrices), `Mat`, `MATSBAIJ`, `MatCreate()`, `MatCreateSeqSBAIJ()`, `MatSetValues()`, `MatCreateBAIJ()`,
2424: `MatGetOwnershipRange()`, `MatGetOwnershipRanges()`, `MatGetOwnershipRangeColumn()`, `MatGetOwnershipRangesColumn()`, `PetscLayout`
2425: @*/
2426: PetscErrorCode MatCreateSBAIJ(MPI_Comm comm, PetscInt bs, PetscInt m, PetscInt n, PetscInt M, PetscInt N, PetscInt d_nz, const PetscInt d_nnz[], PetscInt o_nz, const PetscInt o_nnz[], Mat *A)
2427: {
2428: PetscMPIInt size;
2430: PetscFunctionBegin;
2431: PetscCall(MatCreate(comm, A));
2432: PetscCall(MatSetSizes(*A, m, n, M, N));
2433: PetscCallMPI(MPI_Comm_size(comm, &size));
2434: if (size > 1) {
2435: PetscCall(MatSetType(*A, MATMPISBAIJ));
2436: PetscCall(MatMPISBAIJSetPreallocation(*A, bs, d_nz, d_nnz, o_nz, o_nnz));
2437: } else {
2438: PetscCall(MatSetType(*A, MATSEQSBAIJ));
2439: PetscCall(MatSeqSBAIJSetPreallocation(*A, bs, d_nz, d_nnz));
2440: }
2441: PetscFunctionReturn(PETSC_SUCCESS);
2442: }
2444: static PetscErrorCode MatDuplicate_MPISBAIJ(Mat matin, MatDuplicateOption cpvalues, Mat *newmat)
2445: {
2446: Mat mat;
2447: Mat_MPISBAIJ *a, *oldmat = (Mat_MPISBAIJ *)matin->data;
2448: PetscInt len = 0, nt, bs = matin->rmap->bs, mbs = oldmat->mbs;
2449: PetscScalar *array;
2451: PetscFunctionBegin;
2452: *newmat = NULL;
2454: PetscCall(MatCreate(PetscObjectComm((PetscObject)matin), &mat));
2455: PetscCall(MatSetSizes(mat, matin->rmap->n, matin->cmap->n, matin->rmap->N, matin->cmap->N));
2456: PetscCall(MatSetType(mat, ((PetscObject)matin)->type_name));
2457: PetscCall(PetscLayoutReference(matin->rmap, &mat->rmap));
2458: PetscCall(PetscLayoutReference(matin->cmap, &mat->cmap));
2460: if (matin->hash_active) {
2461: PetscCall(MatSetUp(mat));
2462: } else {
2463: mat->factortype = matin->factortype;
2464: mat->preallocated = PETSC_TRUE;
2465: mat->assembled = PETSC_TRUE;
2466: mat->insertmode = NOT_SET_VALUES;
2468: a = (Mat_MPISBAIJ *)mat->data;
2469: a->bs2 = oldmat->bs2;
2470: a->mbs = oldmat->mbs;
2471: a->nbs = oldmat->nbs;
2472: a->Mbs = oldmat->Mbs;
2473: a->Nbs = oldmat->Nbs;
2475: a->size = oldmat->size;
2476: a->rank = oldmat->rank;
2477: a->donotstash = oldmat->donotstash;
2478: a->roworiented = oldmat->roworiented;
2479: a->rowindices = NULL;
2480: a->rowvalues = NULL;
2481: a->getrowactive = PETSC_FALSE;
2482: a->barray = NULL;
2483: a->rstartbs = oldmat->rstartbs;
2484: a->rendbs = oldmat->rendbs;
2485: a->cstartbs = oldmat->cstartbs;
2486: a->cendbs = oldmat->cendbs;
2488: /* hash table stuff */
2489: a->ht = NULL;
2490: a->hd = NULL;
2491: a->ht_size = 0;
2492: a->ht_flag = oldmat->ht_flag;
2493: a->ht_fact = oldmat->ht_fact;
2494: a->ht_total_ct = 0;
2495: a->ht_insert_ct = 0;
2497: PetscCall(PetscArraycpy(a->rangebs, oldmat->rangebs, a->size + 2));
2498: if (oldmat->colmap) {
2499: #if defined(PETSC_USE_CTABLE)
2500: PetscCall(PetscHMapIDuplicate(oldmat->colmap, &a->colmap));
2501: #else
2502: PetscCall(PetscMalloc1(a->Nbs, &a->colmap));
2503: PetscCall(PetscArraycpy(a->colmap, oldmat->colmap, a->Nbs));
2504: #endif
2505: } else a->colmap = NULL;
2507: if (oldmat->garray && (len = ((Mat_SeqBAIJ *)oldmat->B->data)->nbs)) {
2508: PetscCall(PetscMalloc1(len, &a->garray));
2509: PetscCall(PetscArraycpy(a->garray, oldmat->garray, len));
2510: } else a->garray = NULL;
2512: PetscCall(MatStashCreate_Private(PetscObjectComm((PetscObject)matin), matin->rmap->bs, &mat->bstash));
2513: PetscCall(VecDuplicate(oldmat->lvec, &a->lvec));
2514: PetscCall(VecScatterCopy(oldmat->Mvctx, &a->Mvctx));
2516: PetscCall(VecDuplicate(oldmat->slvec0, &a->slvec0));
2517: PetscCall(VecDuplicate(oldmat->slvec1, &a->slvec1));
2519: PetscCall(VecGetLocalSize(a->slvec1, &nt));
2520: PetscCall(VecGetArray(a->slvec1, &array));
2521: PetscCall(VecCreateSeqWithArray(PETSC_COMM_SELF, 1, bs * mbs, array, &a->slvec1a));
2522: PetscCall(VecCreateSeqWithArray(PETSC_COMM_SELF, 1, nt - bs * mbs, array + bs * mbs, &a->slvec1b));
2523: PetscCall(VecRestoreArray(a->slvec1, &array));
2524: PetscCall(VecGetArray(a->slvec0, &array));
2525: PetscCall(VecCreateSeqWithArray(PETSC_COMM_SELF, 1, nt - bs * mbs, array + bs * mbs, &a->slvec0b));
2526: PetscCall(VecRestoreArray(a->slvec0, &array));
2528: /* ierr = VecScatterCopy(oldmat->sMvctx,&a->sMvctx); - not written yet, replaced by the lazy trick: */
2529: PetscCall(PetscObjectReference((PetscObject)oldmat->sMvctx));
2530: a->sMvctx = oldmat->sMvctx;
2532: PetscCall(MatDuplicate(oldmat->A, cpvalues, &a->A));
2533: PetscCall(MatDuplicate(oldmat->B, cpvalues, &a->B));
2534: }
2535: PetscCall(PetscFunctionListDuplicate(((PetscObject)matin)->qlist, &((PetscObject)mat)->qlist));
2536: *newmat = mat;
2537: PetscFunctionReturn(PETSC_SUCCESS);
2538: }
2540: /* Used for both MPIBAIJ and MPISBAIJ matrices */
2541: #define MatLoad_MPISBAIJ_Binary MatLoad_MPIBAIJ_Binary
2543: static PetscErrorCode MatLoad_MPISBAIJ(Mat mat, PetscViewer viewer)
2544: {
2545: PetscBool isbinary;
2547: PetscFunctionBegin;
2548: PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERBINARY, &isbinary));
2549: PetscCheck(isbinary, PetscObjectComm((PetscObject)viewer), PETSC_ERR_SUP, "Viewer type %s not yet supported for reading %s matrices", ((PetscObject)viewer)->type_name, ((PetscObject)mat)->type_name);
2550: PetscCall(MatLoad_MPISBAIJ_Binary(mat, viewer));
2551: PetscFunctionReturn(PETSC_SUCCESS);
2552: }
2554: static PetscErrorCode MatGetRowMaxAbs_MPISBAIJ(Mat A, Vec v, PetscInt idx[])
2555: {
2556: Mat_MPISBAIJ *a = (Mat_MPISBAIJ *)A->data;
2557: Mat_SeqBAIJ *b = (Mat_SeqBAIJ *)a->B->data;
2558: PetscReal atmp;
2559: PetscReal *work, *svalues, *rvalues;
2560: PetscInt i, bs, mbs, *bi, *bj, brow, j, ncols, krow, kcol, col, row, Mbs, bcol;
2561: PetscMPIInt rank, size;
2562: PetscInt *rowners_bs, count, source;
2563: PetscScalar *va;
2564: MatScalar *ba;
2565: MPI_Status stat;
2567: PetscFunctionBegin;
2568: PetscCheck(!idx, PETSC_COMM_SELF, PETSC_ERR_SUP, "Send email to petsc-maint@mcs.anl.gov");
2569: PetscCall(MatGetRowMaxAbs(a->A, v, NULL));
2570: PetscCall(VecGetArray(v, &va));
2572: PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)A), &size));
2573: PetscCallMPI(MPI_Comm_rank(PetscObjectComm((PetscObject)A), &rank));
2575: bs = A->rmap->bs;
2576: mbs = a->mbs;
2577: Mbs = a->Mbs;
2578: ba = b->a;
2579: bi = b->i;
2580: bj = b->j;
2582: /* find ownerships */
2583: rowners_bs = A->rmap->range;
2585: /* each proc creates an array to be distributed */
2586: PetscCall(PetscCalloc1(bs * Mbs, &work));
2588: /* row_max for B */
2589: if (rank != size - 1) {
2590: for (i = 0; i < mbs; i++) {
2591: ncols = bi[1] - bi[0];
2592: bi++;
2593: brow = bs * i;
2594: for (j = 0; j < ncols; j++) {
2595: bcol = bs * (*bj);
2596: for (kcol = 0; kcol < bs; kcol++) {
2597: col = bcol + kcol; /* local col index */
2598: col += rowners_bs[rank + 1]; /* global col index */
2599: for (krow = 0; krow < bs; krow++) {
2600: atmp = PetscAbsScalar(*ba);
2601: ba++;
2602: row = brow + krow; /* local row index */
2603: if (PetscRealPart(va[row]) < atmp) va[row] = atmp;
2604: if (work[col] < atmp) work[col] = atmp;
2605: }
2606: }
2607: bj++;
2608: }
2609: }
2611: /* send values to its owners */
2612: for (PetscMPIInt dest = rank + 1; dest < size; dest++) {
2613: svalues = work + rowners_bs[dest];
2614: count = rowners_bs[dest + 1] - rowners_bs[dest];
2615: PetscCallMPI(MPIU_Send(svalues, count, MPIU_REAL, dest, rank, PetscObjectComm((PetscObject)A)));
2616: }
2617: }
2619: /* receive values */
2620: if (rank) {
2621: rvalues = work;
2622: count = rowners_bs[rank + 1] - rowners_bs[rank];
2623: for (source = 0; source < rank; source++) {
2624: PetscCallMPI(MPIU_Recv(rvalues, count, MPIU_REAL, MPI_ANY_SOURCE, MPI_ANY_TAG, PetscObjectComm((PetscObject)A), &stat));
2625: /* process values */
2626: for (i = 0; i < count; i++) {
2627: if (PetscRealPart(va[i]) < rvalues[i]) va[i] = rvalues[i];
2628: }
2629: }
2630: }
2632: PetscCall(VecRestoreArray(v, &va));
2633: PetscCall(PetscFree(work));
2634: PetscFunctionReturn(PETSC_SUCCESS);
2635: }
2637: static PetscErrorCode MatSOR_MPISBAIJ(Mat matin, Vec bb, PetscReal omega, MatSORType flag, PetscReal fshift, PetscInt its, PetscInt lits, Vec xx)
2638: {
2639: Mat_MPISBAIJ *mat = (Mat_MPISBAIJ *)matin->data;
2640: PetscInt mbs = mat->mbs, bs = matin->rmap->bs;
2641: PetscScalar *x, *ptr, *from;
2642: Vec bb1;
2643: const PetscScalar *b;
2645: PetscFunctionBegin;
2646: PetscCheck(its > 0 && lits > 0, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Relaxation requires global its %" PetscInt_FMT " and local its %" PetscInt_FMT " both positive", its, lits);
2647: PetscCheck(bs <= 1, PETSC_COMM_SELF, PETSC_ERR_SUP, "SSOR for block size > 1 is not yet implemented");
2649: if (flag == SOR_APPLY_UPPER) {
2650: PetscCall((*mat->A->ops->sor)(mat->A, bb, omega, flag, fshift, lits, 1, xx));
2651: PetscFunctionReturn(PETSC_SUCCESS);
2652: }
2654: if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) {
2655: if (flag & SOR_ZERO_INITIAL_GUESS) {
2656: PetscCall((*mat->A->ops->sor)(mat->A, bb, omega, flag, fshift, lits, lits, xx));
2657: its--;
2658: }
2660: PetscCall(VecDuplicate(bb, &bb1));
2661: while (its--) {
2662: /* lower triangular part: slvec0b = - B^T*xx */
2663: PetscCall((*mat->B->ops->multtranspose)(mat->B, xx, mat->slvec0b));
2665: /* copy xx into slvec0a */
2666: PetscCall(VecGetArray(mat->slvec0, &ptr));
2667: PetscCall(VecGetArray(xx, &x));
2668: PetscCall(PetscArraycpy(ptr, x, bs * mbs));
2669: PetscCall(VecRestoreArray(mat->slvec0, &ptr));
2671: PetscCall(VecScale(mat->slvec0, -1.0));
2673: /* copy bb into slvec1a */
2674: PetscCall(VecGetArray(mat->slvec1, &ptr));
2675: PetscCall(VecGetArrayRead(bb, &b));
2676: PetscCall(PetscArraycpy(ptr, b, bs * mbs));
2677: PetscCall(VecRestoreArray(mat->slvec1, &ptr));
2679: /* set slvec1b = 0 */
2680: PetscCall(PetscObjectStateIncrease((PetscObject)mat->slvec1b));
2681: PetscCall(VecZeroEntries(mat->slvec1b));
2683: PetscCall(VecScatterBegin(mat->sMvctx, mat->slvec0, mat->slvec1, ADD_VALUES, SCATTER_FORWARD));
2684: PetscCall(VecRestoreArray(xx, &x));
2685: PetscCall(VecRestoreArrayRead(bb, &b));
2686: PetscCall(VecScatterEnd(mat->sMvctx, mat->slvec0, mat->slvec1, ADD_VALUES, SCATTER_FORWARD));
2688: /* upper triangular part: bb1 = bb1 - B*x */
2689: PetscCall((*mat->B->ops->multadd)(mat->B, mat->slvec1b, mat->slvec1a, bb1));
2691: /* local diagonal sweep */
2692: PetscCall((*mat->A->ops->sor)(mat->A, bb1, omega, SOR_SYMMETRIC_SWEEP, fshift, lits, lits, xx));
2693: }
2694: PetscCall(VecDestroy(&bb1));
2695: } else if ((flag & SOR_LOCAL_FORWARD_SWEEP) && (its == 1) && (flag & SOR_ZERO_INITIAL_GUESS)) {
2696: PetscCall((*mat->A->ops->sor)(mat->A, bb, omega, flag, fshift, lits, 1, xx));
2697: } else if ((flag & SOR_LOCAL_BACKWARD_SWEEP) && (its == 1) && (flag & SOR_ZERO_INITIAL_GUESS)) {
2698: PetscCall((*mat->A->ops->sor)(mat->A, bb, omega, flag, fshift, lits, 1, xx));
2699: } else if (flag & SOR_EISENSTAT) {
2700: Vec xx1;
2701: PetscBool hasop;
2702: const PetscScalar *diag;
2703: PetscScalar *sl, scale = (omega - 2.0) / omega;
2704: PetscInt i, n;
2706: if (!mat->xx1) {
2707: PetscCall(VecDuplicate(bb, &mat->xx1));
2708: PetscCall(VecDuplicate(bb, &mat->bb1));
2709: }
2710: xx1 = mat->xx1;
2711: bb1 = mat->bb1;
2713: PetscCall((*mat->A->ops->sor)(mat->A, bb, omega, (MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP), fshift, lits, 1, xx));
2715: if (!mat->diag) {
2716: /* this is wrong for same matrix with new nonzero values */
2717: PetscCall(MatCreateVecs(matin, &mat->diag, NULL));
2718: PetscCall(MatGetDiagonal(matin, mat->diag));
2719: }
2720: PetscCall(MatHasOperation(matin, MATOP_MULT_DIAGONAL_BLOCK, &hasop));
2722: if (hasop) {
2723: PetscCall(MatMultDiagonalBlock(matin, xx, bb1));
2724: PetscCall(VecAYPX(mat->slvec1a, scale, bb));
2725: } else {
2726: /*
2727: These two lines are replaced by code that may be a bit faster for a good compiler
2728: PetscCall(VecPointwiseMult(mat->slvec1a,mat->diag,xx));
2729: PetscCall(VecAYPX(mat->slvec1a,scale,bb));
2730: */
2731: PetscCall(VecGetArray(mat->slvec1a, &sl));
2732: PetscCall(VecGetArrayRead(mat->diag, &diag));
2733: PetscCall(VecGetArrayRead(bb, &b));
2734: PetscCall(VecGetArray(xx, &x));
2735: PetscCall(VecGetLocalSize(xx, &n));
2736: if (omega == 1.0) {
2737: for (i = 0; i < n; i++) sl[i] = b[i] - diag[i] * x[i];
2738: PetscCall(PetscLogFlops(2.0 * n));
2739: } else {
2740: for (i = 0; i < n; i++) sl[i] = b[i] + scale * diag[i] * x[i];
2741: PetscCall(PetscLogFlops(3.0 * n));
2742: }
2743: PetscCall(VecRestoreArray(mat->slvec1a, &sl));
2744: PetscCall(VecRestoreArrayRead(mat->diag, &diag));
2745: PetscCall(VecRestoreArrayRead(bb, &b));
2746: PetscCall(VecRestoreArray(xx, &x));
2747: }
2749: /* multiply off-diagonal portion of matrix */
2750: PetscCall(PetscObjectStateIncrease((PetscObject)mat->slvec1b));
2751: PetscCall(VecZeroEntries(mat->slvec1b));
2752: PetscCall((*mat->B->ops->multtranspose)(mat->B, xx, mat->slvec0b));
2753: PetscCall(VecGetArray(mat->slvec0, &from));
2754: PetscCall(VecGetArray(xx, &x));
2755: PetscCall(PetscArraycpy(from, x, bs * mbs));
2756: PetscCall(VecRestoreArray(mat->slvec0, &from));
2757: PetscCall(VecRestoreArray(xx, &x));
2758: PetscCall(VecScatterBegin(mat->sMvctx, mat->slvec0, mat->slvec1, ADD_VALUES, SCATTER_FORWARD));
2759: PetscCall(VecScatterEnd(mat->sMvctx, mat->slvec0, mat->slvec1, ADD_VALUES, SCATTER_FORWARD));
2760: PetscCall((*mat->B->ops->multadd)(mat->B, mat->slvec1b, mat->slvec1a, mat->slvec1a));
2762: /* local sweep */
2763: PetscCall((*mat->A->ops->sor)(mat->A, mat->slvec1a, omega, (MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP), fshift, lits, 1, xx1));
2764: PetscCall(VecAXPY(xx, 1.0, xx1));
2765: } else SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP, "MatSORType is not supported for SBAIJ matrix format");
2766: PetscFunctionReturn(PETSC_SUCCESS);
2767: }
2769: /*@
2770: MatCreateMPISBAIJWithArrays - creates a `MATMPISBAIJ` matrix using arrays that contain in standard CSR format for the local rows.
2772: Collective
2774: Input Parameters:
2775: + comm - MPI communicator
2776: . bs - the block size, only a block size of 1 is supported
2777: . m - number of local rows (Cannot be `PETSC_DECIDE`)
2778: . n - This value should be the same as the local size used in creating the
2779: x vector for the matrix-vector product $ y = Ax $. (or `PETSC_DECIDE` to have
2780: calculated if `N` is given) For square matrices `n` is almost always `m`.
2781: . M - number of global rows (or `PETSC_DETERMINE` to have calculated if `m` is given)
2782: . N - number of global columns (or `PETSC_DETERMINE` to have calculated if `n` is given)
2783: . i - row indices; that is i[0] = 0, i[row] = i[row-1] + number of block elements in that row block row of the matrix
2784: . j - column indices
2785: - a - matrix values
2787: Output Parameter:
2788: . mat - the matrix
2790: Level: intermediate
2792: Notes:
2793: The `i`, `j`, and `a` arrays ARE copied by this routine into the internal format used by PETSc;
2794: thus you CANNOT change the matrix entries by changing the values of `a` after you have
2795: called this routine. Use `MatCreateMPIAIJWithSplitArrays()` to avoid needing to copy the arrays.
2797: The `i` and `j` indices are 0 based, and `i` indices are indices corresponding to the local `j` array.
2799: .seealso: [](ch_matrices), `Mat`, `MATMPISBAIJ`, `MatCreate()`, `MatCreateSeqAIJ()`, `MatSetValues()`, `MatMPIAIJSetPreallocation()`, `MatMPIAIJSetPreallocationCSR()`,
2800: `MATMPIAIJ`, `MatCreateAIJ()`, `MatCreateMPIAIJWithSplitArrays()`, `MatMPISBAIJSetPreallocationCSR()`
2801: @*/
2802: PetscErrorCode MatCreateMPISBAIJWithArrays(MPI_Comm comm, PetscInt bs, PetscInt m, PetscInt n, PetscInt M, PetscInt N, const PetscInt i[], const PetscInt j[], const PetscScalar a[], Mat *mat)
2803: {
2804: PetscFunctionBegin;
2805: PetscCheck(!i[0], PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "i (row indices) must start with 0");
2806: PetscCheck(m >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "local number of rows (m) cannot be PETSC_DECIDE, or negative");
2807: PetscCall(MatCreate(comm, mat));
2808: PetscCall(MatSetSizes(*mat, m, n, M, N));
2809: PetscCall(MatSetType(*mat, MATMPISBAIJ));
2810: PetscCall(MatMPISBAIJSetPreallocationCSR(*mat, bs, i, j, a));
2811: PetscFunctionReturn(PETSC_SUCCESS);
2812: }
2814: /*@
2815: MatMPISBAIJSetPreallocationCSR - Creates a sparse parallel matrix in `MATMPISBAIJ` format using the given nonzero structure and (optional) numerical values
2817: Collective
2819: Input Parameters:
2820: + B - the matrix
2821: . bs - the block size
2822: . i - the indices into `j` for the start of each local row (indices start with zero)
2823: . j - the column indices for each local row (indices start with zero) these must be sorted for each row
2824: - v - optional values in the matrix, pass `NULL` if not provided
2826: Level: advanced
2828: Notes:
2829: The `i`, `j`, and `v` arrays ARE copied by this routine into the internal format used by PETSc;
2830: thus you CANNOT change the matrix entries by changing the values of `v` after you have
2831: called this routine.
2833: Though this routine has Preallocation() in the name it also sets the exact nonzero locations of the matrix entries
2834: and usually the numerical values as well
2836: Any entries passed in that are below the diagonal are ignored
2838: .seealso: [](ch_matrices), `Mat`, `MATMPISBAIJ`, `MatCreate()`, `MatCreateSeqAIJ()`, `MatSetValues()`, `MatMPIBAIJSetPreallocation()`, `MatCreateAIJ()`, `MATMPIAIJ`,
2839: `MatCreateMPISBAIJWithArrays()`
2840: @*/
2841: PetscErrorCode MatMPISBAIJSetPreallocationCSR(Mat B, PetscInt bs, const PetscInt i[], const PetscInt j[], const PetscScalar v[])
2842: {
2843: PetscFunctionBegin;
2844: PetscTryMethod(B, "MatMPISBAIJSetPreallocationCSR_C", (Mat, PetscInt, const PetscInt[], const PetscInt[], const PetscScalar[]), (B, bs, i, j, v));
2845: PetscFunctionReturn(PETSC_SUCCESS);
2846: }
2848: PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPISBAIJ(MPI_Comm comm, Mat inmat, PetscInt n, MatReuse scall, Mat *outmat)
2849: {
2850: PetscInt m, N, i, rstart, nnz, Ii, bs, cbs;
2851: PetscInt *indx;
2852: PetscScalar *values;
2854: PetscFunctionBegin;
2855: PetscCall(MatGetSize(inmat, &m, &N));
2856: if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */
2857: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)inmat->data;
2858: PetscInt *dnz, *onz, mbs, Nbs, nbs;
2859: PetscInt *bindx, rmax = a->rmax, j;
2860: PetscMPIInt rank, size;
2862: PetscCall(MatGetBlockSizes(inmat, &bs, &cbs));
2863: mbs = m / bs;
2864: Nbs = N / cbs;
2865: if (n == PETSC_DECIDE) PetscCall(PetscSplitOwnershipBlock(comm, cbs, &n, &N));
2866: nbs = n / cbs;
2868: PetscCall(PetscMalloc1(rmax, &bindx));
2869: MatPreallocateBegin(comm, mbs, nbs, dnz, onz); /* inline function, output __end and __rstart are used below */
2871: PetscCallMPI(MPI_Comm_rank(comm, &rank));
2872: PetscCallMPI(MPI_Comm_rank(comm, &size));
2873: if (rank == size - 1) {
2874: /* Check sum(nbs) = Nbs */
2875: PetscCheck(__end == Nbs, PETSC_COMM_SELF, PETSC_ERR_ARG_INCOMP, "Sum of local block columns %" PetscInt_FMT " != global block columns %" PetscInt_FMT, __end, Nbs);
2876: }
2878: rstart = __rstart; /* block rstart of *outmat; see inline function MatPreallocateBegin */
2879: PetscCall(MatSetOption(inmat, MAT_GETROW_UPPERTRIANGULAR, PETSC_TRUE));
2880: for (i = 0; i < mbs; i++) {
2881: PetscCall(MatGetRow_SeqSBAIJ(inmat, i * bs, &nnz, &indx, NULL)); /* non-blocked nnz and indx */
2882: nnz = nnz / bs;
2883: for (j = 0; j < nnz; j++) bindx[j] = indx[j * bs] / bs;
2884: PetscCall(MatPreallocateSet(i + rstart, nnz, bindx, dnz, onz));
2885: PetscCall(MatRestoreRow_SeqSBAIJ(inmat, i * bs, &nnz, &indx, NULL));
2886: }
2887: PetscCall(MatSetOption(inmat, MAT_GETROW_UPPERTRIANGULAR, PETSC_FALSE));
2888: PetscCall(PetscFree(bindx));
2890: PetscCall(MatCreate(comm, outmat));
2891: PetscCall(MatSetSizes(*outmat, m, n, PETSC_DETERMINE, PETSC_DETERMINE));
2892: PetscCall(MatSetBlockSizes(*outmat, bs, cbs));
2893: PetscCall(MatSetType(*outmat, MATSBAIJ));
2894: PetscCall(MatSeqSBAIJSetPreallocation(*outmat, bs, 0, dnz));
2895: PetscCall(MatMPISBAIJSetPreallocation(*outmat, bs, 0, dnz, 0, onz));
2896: MatPreallocateEnd(dnz, onz);
2897: }
2899: /* numeric phase */
2900: PetscCall(MatGetBlockSizes(inmat, &bs, &cbs));
2901: PetscCall(MatGetOwnershipRange(*outmat, &rstart, NULL));
2903: PetscCall(MatSetOption(inmat, MAT_GETROW_UPPERTRIANGULAR, PETSC_TRUE));
2904: for (i = 0; i < m; i++) {
2905: PetscCall(MatGetRow_SeqSBAIJ(inmat, i, &nnz, &indx, &values));
2906: Ii = i + rstart;
2907: PetscCall(MatSetValues(*outmat, 1, &Ii, nnz, indx, values, INSERT_VALUES));
2908: PetscCall(MatRestoreRow_SeqSBAIJ(inmat, i, &nnz, &indx, &values));
2909: }
2910: PetscCall(MatSetOption(inmat, MAT_GETROW_UPPERTRIANGULAR, PETSC_FALSE));
2911: PetscCall(MatAssemblyBegin(*outmat, MAT_FINAL_ASSEMBLY));
2912: PetscCall(MatAssemblyEnd(*outmat, MAT_FINAL_ASSEMBLY));
2913: PetscFunctionReturn(PETSC_SUCCESS);
2914: }